Material readiness assessment system

Abstract

The present invention relates to a substance preparation evaluation system, providing an automated substance preparation and evaluation system and method for preparing and evaluating a fluid substance, such as a sample with a bodily fluid, in a container and / or a dispensing tip. The system and method can detect volume, evaluate integrity and check particle concentration in the container and / or the dispensing tip.

Description

[0001] This application is a divisional application of Chinese patent application No. 201780073459.6, filed on October 27, 2017, entitled "Material Preparation Evaluation System".

[0002] Cross-referencing of related patent applications

[0003] This application was filed as a PCT international patent application on October 27, 2017, and claims priority to U.S. Patent Application Serial No. 62 / 414,655, filed on October 28, 2016, and U.S. Patent Application Serial No. 62 / 525,948, filed on June 28, 2017, the disclosures of which are incorporated herein by reference in their entirety. Technical Field

[0004] This invention relates generally to the field of automated material preparation and evaluation. Specifically, it relates to methods and systems for evaluating fluid substances (such as samples containing bodily fluids) in containers and / or dispensing tips. Furthermore, it relates to computer program elements for instructing computing devices and / or processing devices to perform steps of any method for evaluating fluid substances. Additionally, it relates to computer-readable media storing such computer program elements. Background Technology

[0005] The background technology of this invention relates to the field of automated material preparation and evaluation. Summary of the Invention

[0006] The object of this invention may be to provide an improved method and system for automatically evaluating fluid substances, which has improved reliability, improved quality, improved accuracy and improved throughput.

[0007] The objectives of the invention are achieved through the subject matter of the independent claims, wherein other embodiments are included in the dependent claims and the following description.

[0008] According to a first aspect of this disclosure, a method for evaluating fluid substances in a container is provided. The method according to the first aspect can refer to a method for operating a dispensing tip evaluation system, as referenced... Figure 1 The exemplary method described herein, and / or the method for operating a sample quality testing device, as referenced, is as follows. Figures 42 to 55 The exemplary method described above. Furthermore, the method according to the first aspect can refer to a method for operating a volume detection system, as referenced... Figures 5 to 15 and / or Figures 9 to 21 The exemplary method described above. Furthermore, the method of the first aspect can refer to the method of operating a correlation data generation system, such as referenced... Figures 8 to 21 The exemplary method described above.

[0009] The method according to the first aspect includes the following steps:

[0010] - Use an image capturing device to capture an image of at least a portion of the container, wherein the image capturing device may include an image capturing unit;

[0011] - Obtain multiple color parameters of at least a portion of the image using at least one computing device and / or at least one processing device; and

[0012] - Based on these multiple color parameters, sample classification results are generated for the fluid substances contained in the container.

[0013] The sample classification result represents and / or indicates the concentration of at least one interfering substance in the fluid substance. Here and below, image capture device and / or image capture unit may refer to, for example, a tip-mounted image capture unit.

[0014] According to one implementation of the method in the first aspect, multiple color parameters are obtained, including:

[0015] - Generate a histogram for at least a portion of an image, the histogram including multiple color channels; and

[0016] - Obtain multiple averages and / or mean values ​​for these multiple color channels, where multiple color parameters include multiple averages for these multiple color channels.

[0017] In this context, the mean and / or average value can be determined for each color channel or a subset of color channels.

[0018] According to one implementation of the method in the first aspect, multiple color parameters are obtained, including:

[0019] - Generate a histogram for at least a portion of an image, the histogram including multiple color channels; and

[0020] - Obtain and / or determine multiple Riemann sums for these multiple color channels, wherein multiple color parameters include multiple Riemann sums for these multiple color channels.

[0021] Specifically, the Riemann sum can be obtained and / or determined for each color channel or a subset of color channels.

[0022] According to one implementation of the method in the first aspect, multiple color parameters are obtained, including:

[0023] - Generate a histogram for at least a portion of the image, the histogram including multiple color channels;

[0024] - Obtain multiple modes for these multiple color channels;

[0025] - Obtain the maximum values ​​for these multiple color channels; and / or

[0026] - Obtain multiple minimum values ​​for these multiple color channels, where multiple color parameters include multiple modes, maximum values, and / or minimum values ​​for these multiple color channels.

[0027] According to one implementation of the method in the first aspect, multiple color parameters are obtained, including:

[0028] - Generate a histogram for at least a portion of the image, the histogram including multiple color channels;

[0029] - Obtain the headers of multiple histograms for these multiple color channels;

[0030] - Obtain the tails of multiple histograms for these multiple color channels;

[0031] - Obtain the percentage of the head of multiple histograms for these multiple color channels; and / or

[0032] - Obtain multiple histogram tail percentages for these multiple color channels, where multiple color parameters include multiple histogram heads, histogram tails, histogram head percentages, and / or histogram tail percentages for these multiple color channels.

[0033] According to one embodiment of the method of the first aspect, the plurality of color parameters include at least one of the following: a plurality of mean values ​​of color channels, a plurality of Riemann sums of color channels, a plurality of modes of color channels, a plurality of maximum values ​​of color channels, a plurality of minimum values ​​of color channels, a plurality of histogram heads of color channels, a plurality of histogram tails of color channels, a plurality of histogram head percentages of color channels, a plurality of histogram tail percentages of color channels, or any combination thereof.

[0034] According to one embodiment of the method of the first aspect, the plurality of color channels include a red component, a green component, and a blue component, for example in the RGB model. However, any other type of color model, such as, for example, the CMYK color model, may also be used.

[0035] According to one embodiment of the method of the first aspect, the sample classification result includes at least one classification identifier, wherein the at least one classification identifier is related to at least a portion of the plurality of color parameters and / or to the concentration of at least one interfering substance in the fluid substance.

[0036] According to one embodiment of the method of the first aspect, the method further includes generating a labeling result based on the sample classification result; wherein the labeling result indicates the quality of the fluid substance. Alternatively or otherwise, the quality of the fluid substance is based on the sample identification result.

[0037] According to one embodiment of the method of the first aspect, the at least one interfering substance is selected from one or more of hemoglobin, jaundice, and lipemia.

[0038] According to one embodiment of the method of the first aspect, the container is a dispensing tip configured to aspirate fluid substances and / or samples.

[0039] According to one embodiment of the method of the first aspect, the image capturing device is configured and / or arranged to capture an image of a portion of the fluid substance and / or the container from the side of the container.

[0040] According to one implementation of the method of the first aspect, the method further includes the following steps:

[0041] - Use at least one computing device to identify and / or determine a reference point in the image, which is associated with the container;

[0042] - Use at least one computing device to identify and / or determine the surface layer of fluid material inside a container in an image;

[0043] - Determine and / or measure the distance between the reference point and the surface layer; and

[0044] - This distance is converted into the volume of the fluid material based on correlation data, which includes information about the correlation between the volume inside the container and the distances from the reference point to multiple surfaces inside the container.

[0045] However, it should be noted that the term "correlation data" can also refer to the formulaic and / or functional relationship between the distance and volume.

[0046] According to one implementation of the method of the first aspect, distance is measured by pixel distance.

[0047] According to one embodiment of the method of the first aspect, the container is configured to draw in a dispensing tip of a fluid substance, wherein identifying the reference point includes identifying and / or determining a reference line formed on the dispensing tip, for example, a reference line formed on the body of the dispensing tip.

[0048] According to one embodiment of the method of the first aspect, reference lines are identified based on pattern matching and / or based on the segmentation of the captured image.

[0049] According to one embodiment of the method of the first aspect, identifying reference lines includes searching for patterns representing reference lines in the captured image.

[0050] According to one embodiment of the method of the first aspect, identifying the reference line includes comparing at least a portion of the captured image with a reference image.

[0051] According to one embodiment of the method of the first aspect, the method further includes determining the matching rate, matching score and / or correlation value between the captured image portion and the reference image.

[0052] According to one implementation of the method of the first aspect, the method further includes the following steps:

[0053] - Supply liquid to another container;

[0054] - Determine the volume of the supplied liquid;

[0055] - Capture another image of the container;

[0056] - Determine the pixel distance between reference points in the image that are associated with another container; and

[0057] - To correlate a given volume with a given pixel distance.

[0058] According to one embodiment of the method of the first aspect, the method further includes generating correlation data based on a determined volume and a determined pixel distance.

[0059] According to one embodiment of the method of the first aspect, correlation data is generated based on multiple correlations between multiple determined pixel distances and multiple determined liquid volumes supplied to the other container.

[0060] According to one embodiment of the method of the first aspect, the supplied liquid comprises a dye solution. Alternatively or otherwise, the volume of the supplied liquid is determined based on spectrophotometry.

[0061] According to one embodiment of the method of the first aspect, determining the volume of the supplied liquid includes determining the mass of the supplied liquid.

[0062] It should be noted that, as mentioned above, any embodiment of the method according to the first aspect can be combined with one or more other embodiments of the method according to the first aspect, as described above. This can allow for particularly advantageous synergistic enhancement effects.

[0063] According to a second aspect of this disclosure, a computer program element is provided that, when executed on a computing device for evaluating a fluid substance, instructs the computing device and / or system to perform steps according to the first aspect and / or any embodiment of the first aspect.

[0064] According to a third aspect of this disclosure, a non-transitory computer-readable medium is provided, on which computer program elements according to a second aspect of this disclosure are stored.

[0065] According to a fourth aspect of this disclosure, a system for evaluating fluid substances is provided. The system according to the fourth aspect may refer to a sophisticated evaluation system, as referenced in [reference needed]. Figure 1 The exemplary system and / or sample quality testing device mentioned above, as referenced Figures 42 to 55 The exemplary device described above. Furthermore, the system according to the fourth aspect can refer to a volume detection system, as referenced... Figure 1 , Figures 6 to 15 and / or Figures 9 to 21 The exemplary system described above. Furthermore, the system according to the fourth aspect can refer to a correlation data generation system, as referenced... Figures 8 to 21 The exemplary system described above.

[0066] The system according to the fourth aspect includes a sample transfer device having a dispensing tip. The sample transfer device may refer to a substance transfer device. The sample transfer device is configured to at least partially engage the dispensing tip and draw fluid substance into the dispensing tip. The system also includes an image capture unit and at least one computing device, which may include and / or refer to a processing device. The image capture unit is configured to capture an image of at least a portion of the fluid substance in the dispensing tip, and the computing device is configured to obtain multiple color parameters of at least a portion of the image and generate a sample classification result of the fluid substance contained in the dispensing tip based on these multiple color parameters, wherein the sample classification result represents and / or indicates the concentration of at least one interfering substance in the fluid substance.

[0067] To reiterate, the system may include a sample aspiration device having a dispensing tip configured to engage the dispensing tip and to draw fluid material into the dispensing tip. The system may also include: an image capture unit configured to capture an image of at least a portion of the fluid material in the dispensing tip; at least one computing device; and at least one computer-readable storage medium storing instructions that, when executed by the at least one computing device, cause the system to: capture an image of at least a portion of the fluid material in the dispensing tip using the image capture unit, obtain a plurality of color parameters of the at least a portion of the image, and generate a sample classification result of the fluid material contained in the dispensing tip based on the plurality of color parameters, the sample classification result representing the concentration of at least one interfering substance in the fluid material.

[0068] According to one embodiment of the system of the fourth aspect, the computing device is further configured and / or the software instructions further enable the system to:

[0069] - Generate a histogram for at least a portion of the image, the histogram including multiple color channels;

[0070] - Obtain multiple average values ​​for these multiple color channels; and / or

[0071] - Obtain multiple Riemann sums for these multiple color channels.

[0072] Among them, multiple color parameters include multiple means and / or multiple Riemann sums for these color channels.

[0073] According to one embodiment of the system in the fourth aspect, the sample classification result includes at least one classification identifier, wherein the at least one classification identifier is related to at least a portion of the plurality of color parameters and / or to the concentration of at least one interfering substance in the fluid substance. The sample classification result may include at least one of a plurality of classification identifiers, which are related to a plurality of color parameters.

[0074] According to one embodiment of the system of the fourth aspect, the computing device is further configured and / or the software instructions further enable the system to:

[0075] - Identify a reference point in the image that is associated with the assignment tip;

[0076] - Identify the surface layer of fluid material within the dispensing tip in the image;

[0077] - Determine and / or measure the distance between the reference point and the surface layer; and

[0078] - This distance is converted into the volume of the fluid material based on correlation data, which includes information about the correlation between the volume within the dispensing tip and the distance from the reference point to multiple surface layers within the dispensing tip.

[0079] The correlation data may also refer to the formula and / or function relationship between the distance and volume.

[0080] According to one embodiment of the system in the fourth aspect, the computing device is configured to determine a reference line formed on the body of the dispensing tip, and to determine a reference point based on the determined reference line. The reference point in the image may include the reference line formed on the body of the dispensing tip.

[0081] According to one embodiment of the system of the fourth aspect, the computing device is configured to determine the reference line based on pattern matching and / or based on the segmentation of the captured image.

[0082] According to one embodiment of the system of the fourth aspect, the computing device is configured to search for and / or identify patterns representing reference lines in the captured image.

[0083] According to one embodiment of the system of the fourth aspect, the computing device is configured to compare at least a portion of the captured image with a reference image.

[0084] According to one embodiment of the system of the fourth aspect, the computing device is configured to determine the matching rate, matching score and / or correlation value between the captured image portion and the reference image.

[0085] According to one embodiment of the system of the fourth aspect, the image capture unit is configured and / or arranged to capture an image of a portion of the fluid substance from the side of the dispensing tip.

[0086] According to one embodiment of the system in the fourth aspect, the system further includes a sample aspiration module, wherein the image capture unit is attached to the sample aspiration module.

[0087] According to one embodiment of the system of the fourth aspect, the system further includes a light source located opposite the image capture unit and on the side of the dispensing tip, wherein the light source is configured to illuminate the dispensing tip from the side of the dispensing tip.

[0088] According to one embodiment of the system of the fourth aspect, the system further includes a light source and a sample transfer module, wherein the light source and image capture unit are attached to the sample transfer module; and / or wherein the light source and image capture unit are configured to move, for example, horizontally together with the sample transfer module, such that an image of the dispensing tip can be captured at any position on the sample transfer module. Specifically, images can be captured at any position along a track and / or along the sample transfer guide of the sample transfer module.

[0089] According to one embodiment of the system of the fourth aspect, the sample aspiration device is configured to aspirate liquid into another dispensing tip, wherein the system is configured to determine the volume of the aspirated liquid, wherein the image capture unit is configured to capture another image of the other dispensing tip, and wherein the computing device is configured to determine the pixel distance between reference points in the image associated with the other dispensing tip, and is configured to correlate the determined volume with the determined pixel distance.

[0090] According to one implementation of the system in the fourth aspect, the computing device is configured to generate correlation data based on the determined volume and the determined pixel distance.

[0091] According to one implementation of the system of the fourth aspect, correlation data is generated based on multiple correlations between multiple determined pixel distances and multiple determined liquid volumes drawn into the other distribution tip.

[0092] According to one embodiment of the system in the fourth aspect, the aspirated liquid includes a dye solution. Alternatively or otherwise, the system is configured to determine the volume of the aspirated liquid based on spectrophotometry.

[0093] According to one embodiment of the system of the fourth aspect, the system is configured to determine the mass of the pumped liquid and determine the volume of the pumped liquid based on the determined mass of the pumped liquid.

[0094] It should be noted that, as stated above, any implementation of the system according to the fourth aspect can be combined with one or more other implementations of the system according to the fourth aspect, as described above. This can allow for particularly advantageous synergistic enhancement effects.

[0095] Furthermore, it should be noted that any feature, function, characteristic, and / or element of the system according to the fourth aspect as described above and below may be a feature, function, characteristic, step, and / or element of the method according to the first aspect as described above and below. Conversely, any feature, function, characteristic, step, and / or element of the method according to the first aspect as described above and below may be a feature, function, characteristic, and / or element of the system according to the fourth aspect as described above and below.

[0096] According to a fifth aspect of this disclosure, a system for evaluating fluid substances is provided. The system according to the fifth aspect can refer to a tip-aligned detection device, as shown in reference... Figures 56 to 58 The exemplary apparatus described above. The system according to the fifth aspect may also refer to a tip evaluation system and / or a volume detection system, as referenced. Figure 1 , Figures 5 to 15 and / or Figures 9 to 21 The exemplary system described above. Furthermore, the system according to the fifth aspect can refer to a correlation data generation system, as referenced... Figures 8 to 21 The exemplary system described above.

[0097] The system according to the fifth aspect includes a sample transfer device configured to at least partially engage a dispensing tip, the sample transfer device being configured to draw fluid material into the dispensing tip, the dispensing tip having at least one reference line. The sample transfer device may refer to a material transfer device. The system further includes: an image capture unit configured to capture an image of at least a portion of the dispensing tip; and at least one computing device, which may include a processing device configured to:

[0098] - Identify at least one reference line for the distribution tip from this portion of the image;

[0099] - Determine at least one characteristic of the at least one reference line; and

[0100] - Compare at least one characteristic of the at least one reference line with a threshold that represents misalignment of the assigned tip.

[0101] The computing device may be configured to determine whether the characteristics of the at least one reference line meet a threshold representing a misalignment of the assignment tip. This misalignment may refer to misalignment relative to the image capture unit and / or relative to the sample suction module.

[0102] The system may also include at least one computer-readable data storage medium storing software instructions that, when executed by at least one processing device and / or a computing device, cause the system to:

[0103] - Identify at least one reference line for the distribution tip from the image of the distribution tip;

[0104] - Obtain one or more properties of the at least one reference line; and

[0105] - Determine whether the characteristics of the at least one reference line meet a threshold that indicates misalignment of the assigned tip.

[0106] According to one embodiment of the system of the fifth aspect, the at least one reference line includes a first reference line and a second reference line formed on the distribution tip.

[0107] According to one embodiment of the system of the fifth aspect, the at least one reference line includes a first reference line and a second reference line formed on the distribution tip, wherein the at least one computing device is further configured and / or the software instructions further enable the system to:

[0108] - Obtain at least one property of the at least one reference line based on the following:

[0109] - Determine and / or calculate the length of the first reference line;

[0110] - Determine and / or calculate the length of the second reference line; and

[0111] - Determine and / or calculate the angle of a straight line relative to at least one of a first reference line and a second reference line, the straight line connecting predetermined points of the first and second reference lines; and

[0112] - Misalignment is determined based on at least one of the length of the first reference line, the length of the second reference line, and the angle of the line, for example, misalignment of the tip relative to the image capture unit and / or relative to the sample suction module.

[0113] According to one embodiment of the system of the fifth aspect, the system is configured and / or the software instructions further cause the system to: prevent the sample aspiration device from drawing fluid material into the dispensing tip in response to determining a misalignment. By way of example, the computing device may be configured to generate and / or output a stop signal in response to determining a misalignment.

[0114] According to one embodiment of the system of the fifth aspect, the at least one computing device is further configured and / or the software instructions further cause the system to: in response to determining a misalignment, mark and / or initiate the drawing of fluid material into the dispensing tip.

[0115] According to one embodiment of the system of the fifth aspect, the at least one computing device is further configured and / or the software instructions further enable the system to:

[0116] - Identify at least one reference line for the distribution tip from this portion of the image;

[0117] - Identify the surface layer of fluid material within the dispensing tip in the image;

[0118] - Determine and / or measure the distance between the at least one reference line and the surface layer; and

[0119] - The volume of the fluid substance is determined by converting the distance into the volume of the fluid substance based on correlation data, which includes information about the correlation between the volume within the dispensing tip and the distance from the at least one reference line to multiple surfaces within the dispensing tip.

[0120] Correlation can also refer to the formula and / or functional relationship between the distance and volume.

[0121] According to one embodiment of the system in the fifth aspect, the computing device is configured to determine the reference line based on pattern matching and / or based on the segmentation of the captured image.

[0122] According to one embodiment of the system in the fifth aspect, the computing device is configured to search for a pattern representing a reference line in the captured image.

[0123] According to one embodiment of the system of the fifth aspect, the computing device is configured to compare at least a portion of the captured image with a reference image.

[0124] According to one embodiment of the system of the fifth aspect, the computing device is configured to determine the matching rate, matching score and / or correlation value between the captured image portion and the reference image.

[0125] According to one embodiment of the system of the fifth aspect, the at least one reference line includes a first reference line and a second reference line formed on the distribution tip, wherein the at least one computing device is further configured and / or the software instructions further enable the system to:

[0126] - Determine and / or calculate the length of the first reference line in the image;

[0127] - Determine and / or calculate the length of the second reference line in the image;

[0128] - Determine and / or calculate the angle of a straight line relative to at least one of a first reference line and a second reference line, the straight line connecting a predetermined point of the first reference line and a predetermined point of the second reference line;

[0129] - A misalignment is determined based on at least one of the lengths of the first reference line, the second reference line, and the angle of the line, for example, a misalignment of the distribution tip relative to the image capture unit and / or relative to the sample suction module; and

[0130] - Adjust the volume of fluid material based on the determined misalignment.

[0131] According to one embodiment of the system in the fifth aspect, misalignment of the dispensing tip includes lateral misalignment and depth misalignment. Lateral misalignment may refer to displacement of the dispensing tip relative to the optical axis of the camera and / or image capture unit. Depth misalignment may refer to displacement of the dispensing tip along the optical axis of the camera and / or image capture unit.

[0132] According to one embodiment of the system of the fifth aspect, the at least one reference line includes a first reference line and a second reference line formed on the distribution tip, wherein the at least one computing device is further configured and / or the software instructions further enable the system to:

[0133] - Identify the predetermined points of the first reference line in the image;

[0134] - Identify the predetermined points of the second reference line in the image;

[0135] - Define an alignment line that connects the predetermined points of the first reference line and the second reference line;

[0136] - Determine the angle of the alignment line relative to at least one of the first reference line and the second reference line; and

[0137] - Compare this angle to a threshold angle value that indicates misalignment of the side of the distribution tip.

[0138] This involves determining whether the angle of the alignment line is less than a threshold angle value, which indicates that the side of the distribution tip is misaligned.

[0139] According to one implementation of the system in the fifth aspect, the predetermined point of the first reference line is the center point of the first reference line in the image, and the predetermined point of the second reference line is the center point of the second reference line in the image.

[0140] According to one embodiment of the system of the fifth aspect, the system is configured and / or the software instructions further cause the system to: prevent the sample transfer device from drawing fluid material into the dispensing tip in response to determining that the angle of the alignment line relative to at least one of the first and second reference lines meets and / or exceeds a threshold angle value. The system and / or computing device may be configured to generate and / or output a stop signal in response to determining that the angle of the alignment line relative to at least one of the first and second reference lines meets and / or exceeds the threshold angle value. Therefore, the system may be configured to prevent the material transfer device and / or sample transfer device from drawing fluid material into the dispensing tip in response to determining that the angle of the alignment line is not less than the threshold angle value.

[0141] According to one embodiment of the system of the fifth aspect, the at least one computing device is further configured and / or the software instructions further cause the system to: mark the aspiration of fluid material into the dispensing tip and / or initiate the aspiration of fluid material into the dispensing tip, for example, by marking the aspiration, in response to determining that the angle of the alignment line relative to at least one of the first reference line and the second reference line meets and / or exceeds a threshold angle value. Thus, the system can be configured to mark the aspiration of fluid material into the dispensing tip in response to determining that the angle of the alignment line is not less than a threshold angle value.

[0142] According to one embodiment of the system of the fifth aspect, the at least one computing device is further configured and / or the software instructions further enable the system to:

[0143] - Determine and / or identify the length of the at least one reference line based on the captured tip image;

[0144] - Obtain the actual length of the at least one reference line;

[0145] - Calculate the ratio between the length of the at least one reference line and the actual length of the at least one reference line; and

[0146] - This ratio is used to determine the depth misalignment of the distribution tip.

[0147] Alternatively or otherwise, the software instructions further enable the system to:

[0148] - Identify the length of the first reference line from the captured tip image;

[0149] - Obtain the actual length of the first reference line;

[0150] - Calculate the ratio between the length of the first reference line and the actual length of the first reference line; and

[0151] - This ratio is used to determine the depth misalignment of the distribution tip.

[0152] According to one embodiment of the system of the fifth aspect, the system is further configured and / or the software instructions further cause the system to adjust the determined volume of the fluid substance based on the ratio.

[0153] According to one embodiment of the system in the fifth aspect, the system further includes a light source and a sample transfer module, wherein the light source and image capture unit are attached to the sample transfer module, and / or wherein the light source and image capture unit are configured to move, for example, horizontally together with the sample transfer module, such that an image of the dispensing tip can be captured at any location on the sample transfer module. By way of example, an image can be captured at any location along a track and / or along the sample transfer guide of the sample transfer module.

[0154] According to one embodiment of the system of the fifth aspect, the sample aspiration device is configured to aspirate liquid into another dispensing tip, wherein the system is configured to determine the volume of the aspirated liquid. An image capture unit is configured to capture another image of the other dispensing tip, wherein a computing device is configured to determine the pixel distance between reference points in the image associated with the other dispensing tip, and is configured to correlate the determined volume with the determined pixel distance.

[0155] According to one implementation of the system in the fifth aspect, the computing device is configured to generate correlation data based on the determined volume and the determined pixel distance.

[0156] According to one implementation of the system of the fifth aspect, correlation data is generated based on multiple correlations between multiple determined pixel distances and multiple determined liquid volumes drawn into the other distribution tip.

[0157] According to one embodiment of the system of the fifth aspect, the aspirated liquid includes a dye solution, and / or the system is configured to determine the volume of the aspirated liquid based on spectrophotometry.

[0158] According to one embodiment of the system of the fifth aspect, the system is configured to determine the mass of the pumped liquid and determine the volume of the pumped liquid based on the determined mass of the pumped liquid.

[0159] It should be noted that, as stated above, any implementation of the system according to the fifth aspect can be combined with one or more other implementations of the system according to the fifth aspect, as described above. This can allow for particularly advantageous synergistic enhancement effects.

[0160] According to a sixth aspect of this disclosure, a method for evaluating fluid substances in a container is provided. The method according to the sixth aspect can refer to a method for operating a tip alignment detection device, for operating a dispensing tip integrity assessment device, for operating a volume detection system, and / or for operating a dispensing tip assessment system, as referenced. Figure 1 , Figures 5 to 15 , Figures 9 to 21 and / or Figures 56 to 68 The exemplary method described above.

[0161] The method according to the sixth aspect includes the following steps:

[0162] - Use an image capture unit to capture an image of at least a portion of a container, wherein the container may be a distribution tip;

[0163] - Using at least one computing device, determine and / or identify a first reference line and a second reference line of the container from an image of the container;

[0164] - Determine and / or obtain at least one characteristic of at least one of the first reference line and the second reference line.

[0165] The at least one characteristic includes at least one of the following: the length of a first reference line; the length of a second reference line; and an angle of a straight line relative to at least one of the first and second reference lines, wherein the straight line connects a predetermined point of the first reference line and a predetermined point of the second reference line. The method according to the sixth aspect further includes the step of comparing at least one characteristic of at least one of the first and second reference lines with a threshold representing misalignment of the distribution tip.

[0166] To reiterate, the method according to aspect six may include the following steps:

[0167] - Use the image capture unit to capture an image of at least a portion of the container;

[0168] - Use at least one computing device to identify the first and second reference lines of the distribution tip from the image of the distribution tip;

[0169] - Obtain one or more characteristics of a first reference line and a second reference line, said characteristics including at least one of the following: the length of the first reference line; the length of the second reference line; and the angle of a straight line relative to the reference line, the straight line connecting predetermined points of the first and second reference lines; and

[0170] - Determine whether the characteristics of the at least one reference line meet a threshold that indicates misalignment of the assigned tip.

[0171] According to one embodiment of the method of the sixth aspect, the first reference line and the second reference line are determined based on pattern matching and / or based on the segmentation of the captured image.

[0172] According to one embodiment of the method of the sixth aspect, determining the first reference line and the second reference line includes searching for patterns representing the first reference line and / or the second reference line in the captured image.

[0173] According to one embodiment of the method of the sixth aspect, determining the first reference line and the second reference line includes comparing at least a portion of the captured image with a reference image.

[0174] According to one embodiment of the method of the sixth aspect, the method further includes determining the matching rate, matching score and / or correlation value between the captured image portion and the reference image.

[0175] According to one embodiment of the method of the sixth aspect, the container contains a fluid substance, wherein the method further includes:

[0176] - Identify the surface layer of fluid material inside the container in the captured image;

[0177] - Determine the distance between at least one of the first and second reference lines and the surface layer; and

[0178] - The volume of the fluid substance is determined by converting the distance into the volume of the fluid substance based on correlation data, which includes information about the correlation between the volume inside the container and the distance from at least one of the first and second reference lines to multiple surfaces inside the container.

[0179] The correlation data may also refer to the formula and / or function relationship between the distance and volume.

[0180] According to one embodiment of the method of the sixth aspect, the method further includes:

[0181] - Determine the length of the first reference line in the image;

[0182] - Determine the length of the second reference line in the image;

[0183] - Determine the angle of a straight line relative to at least one of a first reference line and a second reference line, the straight line connecting a predetermined point of the first reference line and a predetermined point of the second reference line;

[0184] - The misalignment of the container is determined based on at least one of the length of the first reference line, the length of the second reference line, and the angle of the straight line; and

[0185] - Adjust the volume of fluid material based on the determined misalignment.

[0186] Here, misalignment can refer to misalignment relative to the image capture unit and / or relative to the sample suction module.

[0187] According to one embodiment of the method of the sixth aspect, misalignment of the container includes lateral misalignment and depth misalignment. Lateral misalignment may refer to displacement of the distribution tip relative to the optical axis of the camera and / or image capture unit, and depth misalignment may refer to displacement of the distribution tip along the optical axis of the camera and / or image capture unit.

[0188] According to one embodiment of the method of the sixth aspect, the method further includes:

[0189] - Identify the predetermined points of the first reference line in the image;

[0190] - Identify the predetermined points of the second reference line in the image;

[0191] - Define an alignment line that connects the predetermined points of the first reference line and the second reference line;

[0192] - Determine the angle of the alignment line relative to at least one of the first reference line and the second reference line; and

[0193] - Compare this angle to a threshold angle value, which indicates that the sides of the container are misaligned.

[0194] According to one embodiment of the method of the sixth aspect, the predetermined point of the first reference line is the center point of the first reference line in the image, and the predetermined point of the second reference line is the center point of the second reference line in the image.

[0195] According to one embodiment of the method of the sixth aspect, the method further includes: preventing the aspiration of fluid material into the container in response to determining that the angle of the alignment line relative to at least one of the first reference line and the second reference line satisfies and / or exceeds a threshold angle value. Therefore, in response to determining that the angle of the alignment line relative to at least one of the first reference line and the second reference line satisfies and / or exceeds a threshold angle value, a stop signal to prevent aspiration can be generated.

[0196] According to one embodiment of the method of the sixth aspect, the method further includes: in response to determining that the angle of the alignment line relative to at least one of the first reference line and the second reference line satisfies and / or exceeds a threshold angle value, marking the aspiration of fluid material into the container and / or initiating the aspiration of fluid material into the container.

[0197] According to one embodiment of the method of the sixth aspect, the method further includes:

[0198] - Determine the length of at least one of the first reference line and the second reference line based on the captured container image;

[0199] -For example, obtain the actual length of at least one of the first reference line and the second reference line from the data storage device;

[0200] - Calculate the ratio between the length of at least one of the first reference line and the second reference line and the actual length of that at least one of the first reference line and the second reference line; and

[0201] - This ratio is used to determine if the container's depth is misaligned.

[0202] According to one embodiment of the method of the sixth aspect, the method further includes adjusting the determined volume of the fluid substance based on the ratio.

[0203] It should be noted that, as stated above, any embodiment of the method according to the sixth aspect can be combined with one or more other embodiments of the method according to the sixth aspect, as described above. This can allow for particularly advantageous synergistic enhancement effects.

[0204] Furthermore, it should be noted that any feature, function, characteristic, and / or element of the system according to the fifth aspect as described above and below may be a feature, function, characteristic, step, and / or element of the method according to the sixth aspect as described above and below. Conversely, any feature, function, characteristic, step, and / or element of the method according to the sixth aspect as described above and below may be a feature, function, characteristic, and / or element of the system according to the fifth aspect as described above and below.

[0205] According to a seventh aspect of this disclosure, a computer program element is provided that, when executed on a computing device for evaluating a fluid substance, instructs the computing device and / or the system to perform the steps of the method according to the sixth aspect.

[0206] According to the eighth aspect of this disclosure, a non-transitory computer-readable medium is provided on which computer program elements according to the seventh aspect are stored.

[0207] According to a ninth aspect of this disclosure, a system for evaluating fluid substances is provided. The system according to the ninth aspect may refer to a particle concentration testing system, as shown in reference... Figures 69 to 79 The exemplary system mentioned refers to a volume detection system, such as the referenced system. Figures 5 to 15 The exemplary system mentioned refers to a correlation data generation system, such as the referenced system. Figures 8 to 21 The exemplary system described herein, and / or the device for detecting the remaining volume of a reaction reservoir, as referenced, is as follows. Figures 32 to 34 The exemplary device described above.

[0208] The system according to the ninth aspect includes: a container holder device configured to support and / or hold one or more containers; a sample transfer device and / or a substance transfer device configured to dispense fluid substance into at least one container on the container holder device; an image capture device configured to capture an image of at least one container on the container holder device; and at least one processing device and / or at least one computing device. The system is configured to:

[0209] - Use a sample transfer device to dispense at least one fluid substance into a container;

[0210] - Use an image capture device to capture images of the containers on the container carrier assembly;

[0211] - Analyze an image of the container using at least one processing device to determine the volume of at least one fluid substance dispensed into the container; and

[0212] - Analyze the image of the container using at least one processing device to determine the particle concentration of the fluid material in the entire volume of the container.

[0213] The system may include at least one computer-readable data storage medium storing software instructions that, when executed by at least one processing device, cause the system to:

[0214] - Dispensing one or more fluid substances into a container;

[0215] - Acquire an image of the container on the container rack assembly;

[0216] - Analyze images of the container to determine the volume of the fluid substance dispensed within it; and

[0217] - Analyze images of the container to determine the particle concentration of the fluid material in the entire volume of the container.

[0218] According to one embodiment of the system of the ninth aspect, the fluid substance of the entire volume includes at least one bodily fluid and / or at least one reagent.

[0219] According to one embodiment of the system of the ninth aspect, the computing device is further configured and / or the software instructions further enable the system to:

[0220] - Use an image capture device to capture and / or obtain a first image of the container after the reagent is dispensed into at least one fluid substance contained therein, wherein the at least one fluid substance includes at least one bodily fluid;

[0221] - Use an image capture device to capture and / or obtain a second image of the container after the added reagent has been mixed with at least one fluid substance in the container;

[0222] - Analyze the first image of the container using at least one processing device to determine the volume of reagent dispensed in the container; and

[0223] - Analyze a second image of the container using at least one processing device to determine the particle concentration of the fluid material in the entire volume of the container.

[0224] According to one implementation of the system in the ninth aspect, the particle concentration includes the concentration of paramagnetic particles.

[0225] According to one embodiment of the system of the ninth aspect, the at least one reagent comprises a chemiluminescent substrate.

[0226] According to one embodiment of the system of the ninth aspect, a first image is captured approximately 0.2 seconds after the reagent is dispensed into the container, and a second image is captured after approximately 6.5 seconds of mixing.

[0227] According to one embodiment of the system of the ninth aspect, the image capturing device is mounted to the container carrier device, and the image capturing device is configured and / or arranged to capture an image of the container from the side of the container.

[0228] According to one embodiment of the system of the ninth aspect, the system also includes a light source, wherein the light source and the image capturing device are mounted to the container bracket device such that the light source is positioned opposite the image capturing device.

[0229] According to one embodiment of the system of the ninth aspect, the container carrier device is a cleaning wheel including a rotatable plate, wherein the rotatable plate is configured to rotate the container to the image capture device.

[0230] According to one embodiment of the system of the ninth aspect, the system is further configured and / or the software instructions further enable the system to detect the presence of a container on a container carrier device, for example, by appropriate hardware and / or software methods.

[0231] According to one embodiment of the system of the ninth aspect, the at least one processing device is configured and / or the software instructions further cause the system to:

[0232] - Identify and / or recognize a reference point in an image, wherein the reference point is associated with a container;

[0233] - Identify and / or recognize the surface of at least one fluid substance within a container in an image;

[0234] - Determine and / or measure the distance between the reference point and the surface layer; and

[0235] - Based on correlation data, the distance is converted into the volume of at least one fluid substance and / or reagent to be distributed, the correlation data including information on the correlation between the volume inside the container and the distance from the reference point to multiple surfaces inside the container.

[0236] According to one implementation of the system in the ninth aspect, determining and / or identifying reference points includes determining and / or identifying the bottom portion of the container.

[0237] According to one implementation of the system in the ninth aspect, distance is measured by pixel distance.

[0238] According to one embodiment of the system of the ninth aspect, the processing device is configured to determine the reference point based on pattern matching and / or based on the segmentation of the captured image.

[0239] According to one embodiment of the system of the ninth aspect, the processing device is configured to search for a pattern representing reference points in the captured image.

[0240] According to one embodiment of the system of the ninth aspect, the processing device is configured to compare at least a portion of the captured image with a reference image.

[0241] According to one embodiment of the system of the ninth aspect, the processing device is configured to determine the matching rate, matching score and / or correlation value between the portion of the captured image and the reference image.

[0242] According to one embodiment of the system of the ninth aspect, the sample aspiration device is configured to aspirate liquid into another container, wherein the system is configured to determine the volume of the aspirated liquid, wherein the image capture unit is configured to capture another image of the other container, and wherein the processing device is configured to determine the pixel distance between reference points in the image associated with the other container, and is configured to correlate the determined volume with the determined pixel distance.

[0243] According to one embodiment of the system of the ninth aspect, the processing device is configured to generate correlation data based on the determined volume and the determined pixel distance.

[0244] According to one implementation of the system of the ninth aspect, correlation data is generated based on multiple correlations between multiple determined pixel distances and multiple determined liquid volumes drawn into the other container.

[0245] According to one embodiment of the system of the ninth aspect, the aspirated liquid includes a dye solution. Alternatively or otherwise, the system is configured to determine the volume of the aspirated liquid based on spectrophotometry.

[0246] According to one embodiment of the system of the ninth aspect, the system is configured to determine the mass of the pumped liquid and determine the volume of the pumped liquid based on the determined mass of the pumped liquid.

[0247] According to one embodiment of the system of the ninth aspect, the at least one computing device is configured and / or the software instructions further cause the system to:

[0248] - Obtain and / or determine the brightness of the fluid substance of the entire volume from an image of the container, for example, based on brightness values ​​received from a sensor and / or, for example, based on image processing;

[0249] - Determine the particle concentration of the fluid material across the entire volume based on the brightness and calibration data of the fluid material;

[0250] - Compare the determined particle concentration with a threshold; and

[0251] - In response to determining that the determined particle concentration is below a threshold, the container containing the full volume of fluid material is marked.

[0252] According to one embodiment of the system of the ninth aspect, the computing device is further configured and / or the software instructions further enable the system to:

[0253] - Use a sample aspiration device to aspirate at least a portion of the fluid substance from the container;

[0254] - Capture a third image of at least a portion of the container using an image capture device;

[0255] - The third image is compared with the reference image using the at least one processing device;

[0256] - Using the at least one processing device, a matching score is determined based on the similarity between the third image and the reference image; and

[0257] - Compare the generated match score with the threshold.

[0258] According to one embodiment of the system of the ninth aspect, the system is further configured to and / or the software instructions further cause the system to use the at least one processing means to determine a region of interest in a third image, wherein comparing the third image includes comparing the region of interest in the third image with at least a portion of a reference image.

[0259] According to one implementation of the system in the ninth aspect, the region of interest includes the area adjacent to the bottom of the container.

[0260] According to one embodiment of the system of the ninth aspect, the computing device is further configured and / or the software instructions further enable the system to:

[0261] - When the matching score is equal to and / or below the threshold, mark the result of aspiration from the container, and / or

[0262] - When the matching score does not exceed the threshold, mark the result of suction from the container.

[0263] According to one embodiment of the system of the ninth aspect, the container carrier device includes a plurality of container slots, wherein each container slot is configured to support a container, and wherein the system is further configured and / or the software instructions further cause the system to:

[0264] - Use an image capture device to capture a fourth image of the container slot at the first position of the container support assembly among the plurality of container slots;

[0265] - The fourth image is compared with the reference image using the at least one processing device;

[0266] - Using the at least one processing device, a matching score is generated based on the similarity between the fourth image and the reference image; and

[0267] - Compare the matching score with the threshold.

[0268] According to one embodiment of the system of the ninth aspect, a matching score exceeding and / or satisfying a threshold indicates that no container exists at the container slot among a plurality of container slots.

[0269] According to one embodiment of the system of the ninth aspect, the system is configured to: remove a container from one of a plurality of container slots when the matching score is below a threshold, and / or the software instructions further cause the system to: remove a container from one of a plurality of container slots when the matching score does not meet the threshold.

[0270] According to one embodiment of the system of the ninth aspect, the system is configured to move the container carrier device to a second position after determining that the matching score exceeds and / or meets a threshold, and / or in response to determining that the matching score exceeds and / or meets the threshold. Alternatively or additionally, the software instructions further cause the system to move the container carrier device to the second position after determining that the matching score exceeds the threshold.

[0271] It should be noted that, as stated above, any implementation of the system according to the ninth aspect can be combined with one or more other implementations of the system according to the ninth aspect, as described above. This can allow for particularly advantageous synergistic enhancement effects.

[0272] According to a tenth aspect of this disclosure, a method for evaluating fluid substances in a container is provided. The method according to the tenth aspect can refer to a method for operating a particle concentration monitoring system, as shown in, for example... Figures 69 to 79The exemplary system described herein, and / or the method for operating a volume detection system, as referenced, for example... Figures 5 to 15 The exemplary method described above.

[0273] The method according to aspect ten includes the following steps:

[0274] - Use a sample transfer device to dispense at least one fluid substance into a container;

[0275] - Use an image capture device to capture and / or obtain an image of at least a portion of a container arranged on a container carrier assembly, the container carrier assembly being configured to support and / or hold one or more containers;

[0276] - Analyze an image of a container using at least one computing device to determine the volume of at least one dispensed fluid substance within the container; and

[0277] - Analyze the image of the container using at least one computing device to determine the particle concentration of the fluid material in the entire volume of the container.

[0278] The term "total volume of fluid substance" may refer to at least one dispensed fluid substance and optionally at least one added reagent.

[0279] According to one embodiment of the method of the tenth aspect, capturing and / or obtaining an image of the container includes:

[0280] - Use an image capture device to capture and / or obtain a first image of the container after the reagent is dispensed into at least one fluid substance contained therein, wherein the at least one fluid substance includes at least one bodily fluid;

[0281] - Use an image capture device to capture and / or obtain a second image of the container after the addition of a reagent (e.g., the added reagent) or the mixing of the reagent with at least one fluid substance in the container.

[0282] Analyzing an image of a container to determine the volume of at least one dispensed fluid substance includes analyzing a first image of the container to determine the volume of the dispensed reagent contained in the container, and analyzing an image of the container to determine the particle concentration of the fluid substance in the total volume includes analyzing a second image of the container to determine the particle concentration of the fluid substance in the total volume of the container.

[0283] It should be noted that, as stated above, any embodiment of the method according to aspect ten can be combined with one or more other embodiments of the method according to aspect ten, as described above. This can allow for particularly advantageous synergistic enhancement effects.

[0284] Furthermore, it should be noted that any feature, function, characteristic, and / or element of the system according to the ninth aspect as described above and below may be a feature, function, characteristic, step, and / or element of the method according to the tenth aspect as described above and below. Conversely, any feature, function, characteristic, step, and / or element of the method according to the tenth aspect as described above and below may be a feature, function, characteristic, and / or element of the system according to the ninth aspect as described above and below.

[0285] According to the eleventh aspect of this disclosure, a computer program element is provided that, when executed on a computing device for evaluating a fluid substance, instructs the computing device and / or the system to perform the steps of the method according to the tenth aspect.

[0286] According to the twelfth aspect of this disclosure, a non-transitory computer-readable medium is provided, on which computer program elements according to the eleventh aspect are stored.

[0287] According to a thirteenth aspect of this disclosure, a method for evaluating fluid substances in a container is provided. The method according to the thirteenth aspect can refer to a method for operating a volume detection system, as shown in reference... Figures 5 to 15 The exemplary method described refers to a method for operating an allocation and adjustment system, as shown in the reference. Figures 35 to 36 The exemplary method described refers to a method for operating a correlation data generation system, as shown in the reference. Figures 8 to 21 The exemplary method described herein, and / or the method for operating the remaining volume detection device, as referenced Figures 32 to 34 The exemplary method described above.

[0288] The method according to aspect thirteen includes the following steps:

[0289] - Use a material dispensing device to dispense fluid materials into containers;

[0290] - Use at least one computing device to determine and / or measure the volume of fluid material in the container;

[0291] - Receive operation information from the material distribution device, which includes the operation parameters of the fluid material distribution device;

[0292] -Target distribution volume for receiving fluid substances;

[0293] - Compare the determined fluid volume with the target distribution volume;

[0294] - Calibration information for the material dispensing device; and

[0295] - Adjust the operating parameters of the material dispensing device according to the calibration information.

[0296] According to one embodiment of the method of aspect thirteen, determining and / or measuring the volume of a fluid substance includes:

[0297] - Use an image capture device to capture an image of at least a portion of the container;

[0298] - Use at least one computing device to identify a reference point in the image, which is associated with the container;

[0299] - Use at least one computing device to identify the surface of the fluid substance inside the container in the image;

[0300] - Determine the distance between the reference point and the surface layer; and

[0301] - This distance is converted into the volume of the fluid material based on correlation data, which includes information about the correlation between the volume inside the container and the distances from the reference point to multiple surfaces inside the container.

[0302] According to one embodiment of the method of aspect thirteen, the method further includes:

[0303] - Supply liquid to another container;

[0304] - Determine the volume of the supplied liquid;

[0305] - Capture another image of the container;

[0306] - Determine the pixel distance between reference points in the image that are associated with another container; and

[0307] - To correlate a given volume with a given pixel distance.

[0308] According to one embodiment of the method of aspect thirteen, the method further includes generating correlation data based on a determined volume and a determined pixel distance.

[0309] According to one embodiment of the method of the thirteenth aspect, correlation data is generated based on multiple correlations between multiple determined pixel distances and multiple determined liquid volumes supplied to the other container.

[0310] According to one embodiment of the method of aspect thirteen, the supplied liquid comprises a dye solution. Alternatively or otherwise, the volume of the supplied liquid is determined based on spectrophotometry.

[0311] According to one embodiment of the method of aspect thirteen, determining the volume of the supplied liquid includes determining the mass of the supplied liquid.

[0312] According to one embodiment of the method of aspect thirteen, the method further includes:

[0313] - To aspirate at least a portion of the fluid substance from the container;

[0314] - Use an image capture device to capture an image of at least a portion of the container;

[0315] - Compare this image with a reference image;

[0316] - Generate a matching score based on the similarity between the image and the reference image.

[0317] According to one embodiment of the method of aspect thirteen, the method further includes:

[0318] - Compare the match score to a threshold; and / or

[0319] - Determine if the matching score exceeds the threshold.

[0320] According to one embodiment of the method of the thirteenth aspect, the method further includes determining a region of interest in an image, wherein comparing images includes comparing the region of interest in the image with at least a portion of a reference image.

[0321] According to one embodiment of the method in aspect thirteen, the region of interest includes the area adjacent to the bottom of the container.

[0322] According to one embodiment of the method of aspect thirteen, the method further includes: marking the result of aspiration from the container when the matching score meets and / or falls below a threshold.

[0323] According to one embodiment of the method of aspect thirteen, the method further includes:

[0324] - Arrange multiple containers in multiple container slots of the container rack assembly;

[0325] - Use an image capture device to capture an image of the container slot at a first position on the container support assembly among the plurality of container slots;

[0326] - Compare this image with a reference image;

[0327] - Generate a matching score based on the similarity between the image and the reference image.

[0328] According to one embodiment of the method of aspect thirteen, the method further includes:

[0329] - Compare the match score to a threshold; and / or

[0330] - Determine that the matching score exceeds and / or meets a threshold, wherein a matching score exceeding the threshold indicates that there is no container at the container slot in one of the multiple container slots.

[0331] According to one embodiment of the method of the thirteenth aspect, the method further includes: removing a container from one of the multiple container slots when the matching score is below a threshold.

[0332] According to one embodiment of the method of the thirteenth aspect, the method further includes: moving the container carrier device to a second position after determining that the matching score exceeds and / or meets the threshold.

[0333] It should be noted that, as stated above, any embodiment of the method according to the thirteenth aspect can be combined with one or more other embodiments of the method according to the thirteenth aspect, as described above. This can allow for particularly advantageous synergistic enhancement effects.

[0334] Furthermore, it should be noted that any feature, function, characteristic, and / or element of the system according to the ninth aspect as described above and below may be a feature, function, characteristic, step, and / or element of the method according to the thirteenth aspect as described above and below. Conversely, any feature, function, characteristic, step, and / or element of the method according to the thirteenth aspect as described above and below may be a feature, function, characteristic, and / or element of the system according to the ninth aspect as described above and below.

[0335] According to the fourteenth aspect of this disclosure, a computer program element is provided that, when executed on a computing device for a system for evaluating fluid substances, instructs the computing device and / or the system to perform the steps of the method according to the thirteenth aspect.

[0336] According to the fifteenth aspect of this disclosure, a non-transitory computer-readable medium is provided, on which computer program elements according to the fourteenth aspect are stored. Attached Figure Description

[0337] Figure 1 This is a block diagram of an exemplary instrument used for analyzing biological specimens.

[0338] Figure 2 schematically shown Figure 1 An example of a biological specimen analysis instrument.

[0339] Figure 3 An exemplary architecture of a computing device that can be used to implement aspects of this disclosure is shown.

[0340] Figure 4 This is a schematic diagram illustrating an exemplary method for immunological analysis.

[0341] Figure 5 yes Figure 1 A block diagram of an example volume detection system.

[0342] Figure 6A flowchart illustrating an exemplary method for operating a volume detection system is provided.

[0343] Figure 7 This shows the execution Figure 6 A flowchart illustrating an exemplary method for operating a volume detection system.

[0344] Figure 8 This is a flowchart illustrating an exemplary method for operating a correlation data generation system to generate correlation data.

[0345] Figure 9 It shows Figure 5 An example of a device for detecting the volume of a dispensing tip.

[0346] Figure 10 An exemplary structure of a sample aspiration system incorporating a dispensing tip volume detection device is schematically shown.

[0347] Figure 11 yes Figure 10 A perspective view of the sample aspiration system.

[0348] Figure 12A yes Figure 10 A side view of the sample aspiration system.

[0349] Figure 12B yes Figure 10 Another side view of the sample aspiration system.

[0350] Figure 13 This is a schematic perspective view of an exemplary distribution tip.

[0351] Figure 14 yes Figure 13 A cross-sectional view of the distal end of the tip of the distribution.

[0352] Figure 15 This is a flowchart illustrating an exemplary method for operating a tip volume detection device.

[0353] Figure 16 This shows the execution Figure 15 A flowchart illustrating an exemplary method for operating a tip volume detection device.

[0354] Figure 17 An exemplary analysis of the captured image of the assigned tip is shown.

[0355] Figure 18 It shows the Figure 17 Analysis of captured images.

[0356] Figure 19 It shows the Figure 17 Analysis of captured images.

[0357] Figure 20 This is an exemplary correlation curve corresponding to tip volume correlation data.

[0358] Figure 21 This is a flowchart illustrating an exemplary method for operating a tip volume correlation data generation system to generate tip volume correlation data.

[0359] Figure 22 It shows Figure 5 Example of a reservoir volume detection device.

[0360] Figure 23 An exemplary container rack device incorporating a container volume detection device is shown.

[0361] Figure 24 yes Figure 23 Another perspective view of the container rack assembly, showing Figure 23 Image capture unit for storage.

[0362] Figure 25 This is a top view of a cleaning wheel with a reservoir volume detection device including a reservoir image capture unit.

[0363] Figure 26 This is a flowchart illustrating an exemplary method of operating a reservoir volume detection device via a cleaning wheel.

[0364] Figure 27 This is a flowchart illustrating an exemplary method for operating a reactor dispensing volume detection device.

[0365] Figure 28 This shows the execution Figure 27 A flowchart illustrating an exemplary method for operating a reaction reservoir dispensing volume detection device.

[0366] Figure 29 An exemplary analysis of a captured image of a reaction reservoir is shown.

[0367] Figure 30 This is an example correlation curve corresponding to the correlation data of the reservoir volume.

[0368] Figure 31 This is a flowchart illustrating an exemplary method for operating a reservoir volume correlation data generation system to generate reservoir volume correlation data.

[0369] Figure 32 This is a flowchart illustrating an exemplary method for detecting the remaining volume of a reaction tank using an operating tank volume detection device.

[0370] Figure 33 This shows the execution Figure 32A flowchart illustrating an exemplary method for operating a reaction reservoir remaining volume detection device.

[0371] Figure 34 An exemplary analysis of a captured image of the reservoir is shown.

[0372] Figure 35 This is a block diagram of an example system in which the dispensing and adjusting device of the reservoir volume detection device operates.

[0373] Figure 36 This shows the operation. Figure 35 A flowchart of an exemplary method for the allocation adjustment device.

[0374] Figure 37 This is a flowchart illustrating an exemplary method of operating a reaction reservoir volume detection device.

[0375] Figure 38 This shows the execution Figure 37 A flowchart illustrating an exemplary method for operating a reaction reservoir detection device.

[0376] Figure 39 An exemplary analysis of a captured image of a reservoir on a cleaning wheel is shown.

[0377] Figure 40 yes Figure 1 A block diagram of an exemplary integrity assessment system.

[0378] Figure 41 yes Figure 40 A block diagram of an exemplary allocation tip integrity assessment device.

[0379] Figure 42 An exemplary sample quality testing device is shown.

[0380] Figure 43 This shows the operation. Figure 42 A flowchart of an exemplary method for a sample quality testing device.

[0381] Figure 44 This shows the operation. Figure 42 A flowchart of an exemplary method for an image evaluation apparatus.

[0382] Figure 45 An exemplary analysis of the captured image is shown.

[0383] Figure 46 This is a flowchart illustrating an exemplary method for finding a region of interest in an image.

[0384] Figure 47 This is a flowchart of an example method for extracting color parameters from an image.

[0385] Figure 48 An exemplary histogram of the image is shown.

[0386] Figure 49 It is used for operation Figure 42 A flowchart of an exemplary method for a classification data generation apparatus.

[0387] Figure 50 This is an example table of interference values ​​analyzed as category labels.

[0388] Figure 51 It is an exemplary set of sample classification identifiers.

[0389] Figure 52 An exemplary color parameter data table for three interfering substances is shown.

[0390] Figure 53 It shows the source such as Figure 52 An exemplary set of sample classifiers for combinations of the first, second, and third interfering factors shown.

[0391] Figure 54 It is shown schematically. Figure 42 A block diagram of an exemplary sorting device.

[0392] Figure 55 This is an example dataset of sample classification results and related labeling results.

[0393] Figure 56 This is a block diagram of an exemplary tip alignment detection device.

[0394] Figure 57 This is a cross-sectional view of an exemplary distribution tip, showing possible tolerances in the distribution tip.

[0395] Figure 58 An exemplary misalignment of the dispensing tip is illustrated schematically.

[0396] Figure 59 The possible types of misalignment of the assignment tip are shown.

[0397] Figure 60A This is an exemplary cross-sectional side view of a dispensing tip that can be used with a tip alignment detection device.

[0398] Figure 60B yes Figure 60A A partial unfolded diagram of the distribution tip.

[0399] Figure 60C is Figure 60A A partial unfolded diagram of the distribution tip.

[0400] Figure 61 This is a flowchart illustrating an exemplary method for evaluating the alignment of assigned tips.

[0401] Figure 62 This is a flowchart illustrating an exemplary method for detecting misalignment of the dispensing tip.

[0402] Figure 63 This is a flowchart illustrating another exemplary method for detecting misalignment of the dispensing tip.

[0403] Figure 64 An exemplary image is shown schematically, illustrating misalignment of the sides of the dispensing tip.

[0404] Figure 65 This is a flowchart illustrating an exemplary method for correcting volume using a second reference line.

[0405] Figure 66 This is a flowchart illustrating another exemplary method for correcting volume using a second reference line.

[0406] Figure 67 The diagram schematically illustrates the depth misalignment of the distribution tip relative to the camera unit.

[0407] Figure 68 This is an exemplary data sheet for volumetric measurements before and after calibration performed by a tip alignment detection device.

[0408] Figure 69 yes Figure 1 A block diagram of an exemplary particle concentration detection system.

[0409] Figure 70 An exemplary image of a reaction reservoir with different particle concentrations is shown.

[0410] Figure 71 This is a block diagram of an exemplary reaction reservoir particle concentration monitoring system.

[0411] Figure 72 This is a flowchart illustrating an exemplary method for measuring the particle concentration in a fluid substance contained in a reaction reservoir.

[0412] Figure 73 This is a flowchart illustrating an exemplary method for generating calibration data.

[0413] Figure 74 This is a table of exemplary substances used to generate calibration data.

[0414] Figure 75 An exemplary calibration curve plotted based on calibration data is shown.

[0415] Figure 76 This is a flowchart illustrating an exemplary method for measuring the particle concentration in a fluid substance contained in a reaction reservoir.

[0416] Figure 77 This is an exemplary table of exemplary concentration thresholds for different analytes.

[0417] Figure 78 This is a flowchart illustrating an exemplary diagnostic function utilizing the particle concentration monitoring system for reaction reservoirs.

[0418] Figure 79 yes Figure 78 A flowchart of another example of the diagnostic function. Detailed Implementation

[0419] Various embodiments will now be described in detail with reference to the accompanying drawings, in which similar reference numerals denote similar parts and components. The mention of various embodiments is not intended to limit the scope of the appended claims. Furthermore, any examples listed in this specification are not intended to be limiting, but merely to set forth a number of possible embodiments with respect to the appended claims.

[0420] Figure 1 This is a block diagram of an exemplary instrument 100 for analyzing biological specimens. In some embodiments, instrument 100 includes a material preparation system 102, a preparation evaluation system 104, and a material evaluation system 106. One or more containers 110 are used with the systems of instrument 100 and include a dispensing tip 112 and a reservoir 114. One or more container holder arrangements 116 disposed in instrument 100 are also shown. Additionally, the preparation evaluation system 104 includes a volume detection system 120, a dispensing tip evaluation system 122, and a holder detection system 126. In some embodiments, the volume detection system 120 utilizes a dispensing tip image capture unit 130 and a reservoir image capture unit 132. In some embodiments, the dispensing tip evaluation system 122 uses the dispensing tip image capture unit 130, and the particle concentration detection system 124 uses the reservoir image capture unit 132. In some embodiments, the holder detection system 126 uses the holder image capture unit 134.

[0421] It should be noted that, as described in the summary section of this disclosure, the system for evaluating fluid substances according to the fourth, fifth, and / or ninth aspects can each refer to the instrument 100 for analyzing biological specimens and / or can each refer to one or more components and / or devices of the instrument 100. Furthermore, as described in the summary section of this disclosure, the method for evaluating fluid substances according to the first, sixth, tenth, and / or thirteenth aspects can each refer to the method for operating the instrument 100 and / or can each refer to the method for operating one or more components and / or devices of the instrument 100.

[0422] The biological specimen analyzer 100 is used to analyze biological specimens for various purposes. In some embodiments, the biological specimen analyzer 100 is configured to analyze blood samples and to collect, test, process, store, and / or transfuse blood and its components.

[0423] Material preparation system 102 is used to prepare one or more substances for further analysis by material evaluation system 106. In some embodiments, material preparation system 102 is used to divide substance 118 into containers 110, draw substance 118 from containers 110, and dispense substance 118 into containers 110.

[0424] The preparation assessment system 104 is used to assess the preparation of a substance for subsequent analysis by the substance assessment system 106. In some embodiments, the preparation assessment system 104 utilizes one or more image capture units to determine whether the substance 118 has been properly prepared for analysis. As described herein, the preparation assessment system 104 provides a direct and simple measurement of the volume or integrity of the substance 118 to determine whether the substance 118 has been properly prepared, enabling the substance assessment system 106 to produce reliable results using the substance 118.

[0425] The material evaluation system 106 is used to evaluate the material 118 prepared by the material preparation system 102. By way of example, the material evaluation system 106 performs the following steps as described in the reference... Figure 2 The aforementioned immunoassay.

[0426] Container 110 is used to prepare one or more substances 118 to be analyzed by substance evaluation system 106. Container 110 can be of various types, such as specimen tubes (also referred to herein as sample tubes), pipette tips, and reservoirs. In some embodiments, container 110 includes a dispensing tip 112 and a reservoir 114.

[0427] Dispensing tip 112 is provided to material preparation system 102 to aliquot or aspirate material 118 from other containers (e.g., reservoir 114). For example, dispensing tip 112 is used to aliquot a sample from a specimen tube or aspirate a sample or reagent from a sample reservoir or reagent reservoir. Reference Figure 13 and Figure 14 An example of the allocation tip 112 is described and shown in more detail.

[0428] The reservoir 114 is provided to the material preparation system 102 to contain the substance 118 for preparation and analysis. In some embodiments, the material preparation system 102 dispenses the substance 118 into the reservoir 114. Examples of reservoirs 114 include sample reservoirs, diluent reservoirs, and reaction reservoirs, which are described in more detail herein.

[0429] The container rack assembly 116 is configured to hold and carry containers 110 at various locations within the instrument 100, allowing the material preparation system 102, the preparation evaluation system 104, and the material evaluation system 106 to use the containers 110 in various ways. Examples of the container rack assembly 116 include reservoir racks (e.g., sample racks, reagent racks, and diluent racks), sample presentation units, reservoir rack units (e.g., sample rack units, reaction reservoir rack units, and reagent rack units), reservoir transfer units (e.g., sample transfer units, reagent transfer units, incubator transfer units, and reaction reservoir transfer units), and reservoir holding plates or wheels (e.g., sample wheels, incubator wheels, and cleaning wheels), see reference. Figure 2 A more detailed description and explanation.

[0430] Substance 118 is prepared, evaluated, and examined in instrument 100 for various tests and analyses. Substance 118 includes any substance that can be equally divided, aspirated, and dispensed in instrument 100. In some embodiments, substance 118 has fluid properties and is therefore referred to herein as a fluid substance. In some embodiments, fluid substance 118 is a single fluid substance. In other embodiments, fluid substance 118 is a mixture of multiple substances.

[0431] The volume detection system 120 of the preparation evaluation system 104 is used to detect the volume of fluid substance 118 in container 110 and determine whether the volume held in container 110 is suitable as a target. As described herein, the volume detection system 120 is configured to detect the volume at dispensing tip 112 using dispensing tip image capture unit 130 and to detect the volume at reservoir 114 using reservoir image capture unit 132.

[0432] The dispensing tip evaluation system 122 of the preparation evaluation system 104 is used to evaluate the integrity of the fluid substance 118. In some embodiments, the dispensing tip evaluation system 122 detects any interfering substances that may interfere with the analysis process and may produce incorrect results. As described herein, the dispensing tip evaluation system 122 is configured to determine the quality of the fluid substance 118 at the dispensing tip 112 and the alignment of the dispensing tip 112 relative to the dispensing tip image capture unit 130 using the dispensing tip image capture unit 130.

[0433] The particle concentration detection system 124 is used to determine the particle concentration in a fluid substance contained in a reservoir, such as a reaction reservoir, sample reservoir, diluent reservoir, colorimetric tube, or any suitable type of reservoir, which is used throughout the process of instrument 100. In some embodiments, the reaction reservoir particle concentration detection system 1700 uses a reservoir image capture unit 132.

[0434] The allocation tip image capture unit 130 is used to capture images of the allocation tip 112 at one or more locations. In some embodiments, the allocation tip image capture unit 130 is fixed at a specific location within the instrument 100. In other embodiments, the allocation tip image capture unit 130 is movably disposed within the instrument 100, and can move independently of other components of the instrument 100 or move together with one or more components of the instrument 100. Some embodiments of the instrument 100 include multiple allocation tip image capture units 130. As described herein, the allocation tip image capture unit 130 may include a camera unit 550 (e.g., Figure 11 ) and camera unit 2550 ( Figure 11 and 67 ).

[0435] The reservoir image capture unit 132 is used to capture images of the reservoir 114 at one or more locations. In some embodiments, the reservoir image capture unit 132 is fixed at a specific location within the instrument 100. In other embodiments, the reservoir image capture unit 132 is movably disposed within the instrument 100, and can move independently of other components of the instrument 100 or move together with one or more components of the instrument 100. Some embodiments of the instrument 100 include multiple reservoir image capture units 132. As described herein, the reservoir tip image capture unit 132 includes a camera unit 730 (e.g., Figure 24 ).

[0436] The container carrier image capture unit 134 is used to capture images of the container carrier assembly 116, with or without the container 110, at one or more locations. In some embodiments, the container carrier image capture unit 134 is fixed at a specific location within the instrument 100. In other embodiments, the container carrier image capture unit 134 is movably disposed within the instrument 100, and can move independently of other components of the instrument 100 or together with one or more components of the instrument 100. Some embodiments of the instrument 100 include multiple container carrier image capture units 134.

[0437] Continue to refer to Figure 1 In some implementations, instrument 100 is used to communicate with management system 136 via data communication network 138. For example, instrument 100 includes communication devices (such as...) Figure 3 The instrument 100 communicates with the management system 136 via the communication device 246.

[0438] In some implementations, the management system 136 is located remotely from instrument 100 and is configured to perform diagnostics based on data from instrument 100. Additionally, instrument 100 may evaluate instrument performance and generate reports. An example of the management system 136 includes one or more computing devices executing a PROSevice remote service application purchased from Beckman Coulter, Inc., Brea, CA.

[0439] Beckman Coulter's PROService remote service application provides a secure and continuous connection between the biosample analysis instrument 100 and a remote diagnostic command center (e.g., management system 136) via a network (e.g., network 138). The biosample analysis instrument 100 can connect to the remote diagnostic command center via the Internet through an Ethernet port, Wi-Fi, or a cellular network.

[0440] Still refer to Figure 1 Data communication network 138 transmits digital data between one or more computing devices, such as between data collection device 108 and data processing system 136. Examples of network 138 include local area networks (LANs) and wide area networks (WANs), such as the Internet. In some embodiments, network 138 includes a wireless communication system, a wired communication system, or a combination of wireless and wired communication systems. In various possible embodiments, wired communication systems may use electrical or optical signals to transmit data. Wireless communication systems typically transmit signals via electromagnetic waves, such as in the form of optical or radio frequency (RF) signals. Wireless communication systems typically include an optical transmitter or RF transmitter for transmitting optical or RF signals and an optical receiver or RF receiver for receiving optical or RF signals. Examples of wireless communication systems include Wi-Fi communication devices (such as those utilizing wireless routers or wireless access points), cellular communication devices (such as those utilizing one or more cellular base stations), and other wireless communication devices.

[0441] Figure 2 schematically shown Figure 1An example of a biological specimen analysis instrument 100 is provided. In the illustrated example, instrument 100 is configured as an immunoassay analyzer. As described above, instrument 100 includes a material preparation system 102, a preparation evaluation system 104, and a material evaluation system 106. In some embodiments, the material preparation system 102 includes a sample supply plate 140, a sample presentation unit 142, a reaction reservoir feeder 144, a reaction reservoir holder unit 146, a sample transfer unit 148, a transfer tip feeder 150, a sample transfer device 152, a sample wheel 158, a reagent holder unit 160, a reagent transfer device 162, a reagent storage device 164, a reagent loading device 166, an incubator transfer unit 170, an incubator 172, a reaction reservoir transfer unit 174, a cleaning wheel 176, and a substrate loading device 180. In some embodiments, the material evaluation system 106 includes a photometric device 190 and an evaluation processing device 192. Some implementations of the material assessment system 106 are also associated with at least some operations performed by the incubator transfer unit 170, incubator 172, reaction reservoir transfer unit 174, cleaning wheel 176, and substrate loading device 180.

[0442] The sample supply plate 140 is configured to receive multiple sample tubes in multiple sample racks. In some embodiments, a user (e.g., a laboratory technician) loads one or more sample tube racks onto the sample supply plate 140. The sample supply plate 140 can move the racks to the sample presentation unit 142 for transfer and receive the transfer racks returned by the sample presentation unit 142 after transfer.

[0443] The sample presentation unit 142 is used to transfer one or more sample tube racks to a designated location. In some embodiments, the sample supply plate 140 is used to provide a sample rack to the sample presentation unit 142. Additionally, the sample presentation unit 142 can be used to identify the sample rack and the sample ID on it. The sample presentation unit 142 moves the sample rack to a sample aspiration position, where a sample pipette bisects the sample tubes in the sample rack. As the sample pipette bisects one sample tube in the sample rack, the sample presentation unit 142 points to another sample tube in the sample rack for the next aspiration. After all sample tubes have been aspirated, the sample presentation unit 142 returns the sample rack to the sample supply plate 140. The sample presentation unit 142 may include a sample rack presentation unit. In other embodiments, the sample presentation unit 142 is configured to transfer a spring tray carrying a single tube. It should be understood that the sample presentation unit 142 is also configured and used for other types of containers, such as cups or reservoirs.

[0444] The reaction reservoir feeder 144 supplies multiple reaction reservoirs to the reaction reservoir carrier unit 146. Users can load a large number of new empty reaction reservoirs into the reaction reservoir feeder 144. In some embodiments, the reaction reservoir feeder 144 is used to orient the reaction reservoirs when supplying them to the reaction reservoir carrier unit 146.

[0445] The reaction reservoir holder unit 146 is used to transfer reaction reservoirs from the reaction reservoir feeder 144 to the sample transfer unit 148. In some embodiments, the reaction reservoir holder unit 146 picks up one or more reaction reservoirs from the reaction reservoir feeder 144 and transfers these reaction reservoirs to the sample transfer unit 148.

[0446] The sample transfer unit 148 is used to transfer empty reaction containers from the reaction container holder unit 146 to the sample wheel 158 and the reagent holder unit 160. Furthermore, the sample transfer unit 148 is used to transfer aliquots of sample containers to the reagent holder unit 160 and to transfer sample containers from the reagent holder unit 160 back to the sample wheel 158. The sample transfer unit 148 can be further used to dispose of sample containers and diluent containers that have been used in a predetermined process.

[0447] The suction tip feeder 150 supplies suction tips to the sample suction device 152. In this document, the suction tip is an example of the dispensing tip 112, and therefore may also be referred to herein as the dispensing tip 112. In some embodiments, multiple suction tips in a sample holder are loaded in an array in the suction tip feeder 150. The suction tips are transferred and engaged with the sample suction device 152 for suction. Once used, the suction tips are disengaged from the sample suction device 152 for disposal, and the sample suction device 152 can be returned to the suction tip feeder 150. Users may discard solid waste, including used suction tips.

[0448] The sample transfer device 152 performs various transfer operations. The sample transfer device 152 receives a transfer tip from the transfer tip feeder 150 and engages the transfer tip with the sample transfer device 152. In some embodiments, the sample transfer device 152 engages the transfer tip by pressing a transfer mandrel into the transfer tube tip and lifting the transfer mandrel that mates with the transfer tube tip. As described herein, some embodiments of the transfer tip may be discarded after a single use or multiple uses.

[0449] In some embodiments, the sample transfer device 152 includes a sample division transfer unit (“sample division gantry”) 152A and a sample precision transfer unit (“sample precision gantry”) 152B.

[0450] The sample aliquoting and transfer unit 152A is used to aliquot a sample from a sample tube located in the sample presentation unit 142 and distribute the aliquots into a sample reservoir on the sample wheel 158. When the aliquoting operation for each sample is complete, the sample aliquoting and transfer unit can discard the used aliquoting tip. As described herein, the sample aliquoting and transfer unit 152A may include a camera unit 550, which is referred to herein by reference, for example... Figure 11 , 12A Further description is provided for 12B.

[0451] The precise sample transfer unit 152B is used to transfer a sample from a sample reservoir located on the reagent holder unit 160. The precise sample transfer unit can then dispense the sample into the reaction reservoir. In some embodiments, the sample can be first dispensed into a diluent reservoir to generate a sample diluent (e.g., a washing buffer provided by the reagent transfer device 162) before dispensing into the reaction reservoir. When the predetermined test is completed, the precise sample transfer unit can discard the used transfer tip. As described herein, the precise sample transfer unit 152B may include a camera unit 2550, which is referred to herein as... Figure 11 , 12A Further descriptions are provided for 12B and 67.

[0452] The sample wheel 158 stores aliquots of sample in a sample reservoir thereon. In some embodiments, the sample wheel 158 is used to maintain the sample at a low temperature, such as about 4-10°C, to reduce changes in analyte concentration due to evaporation. If additional testing is required, the sample reservoir can be transferred back to the sample wheel 158 after reagent aspiration.

[0453] The reagent rack unit 160 is configured to support multiple reservoirs and transfer them to different locations. In some embodiments, the reagent rack unit 160 is configured to hold multiple reservoirs (e.g., three or four reservoirs) that can be used simultaneously by each reagent pipette of the reagent transfer device 162. In some embodiments, the reagent rack unit 160 is controlled at about 30°C to 40°C by heating. In other embodiments, for example, the reagent rack unit 160 is maintained at about 37°C to ensure consistent enzyme kinetics.

[0454] In some embodiments, the reagent holder unit 160 is configured to hold the reaction reservoir, diluent reservoir, and sample reservoir, and to transport the reservoirs for sample and reagent transfer. In some embodiments, the reagent holder unit 160 includes a holder shuttle movable along a predetermined path. For example, the reagent holder unit 160 moves to proximity to the sample transfer unit 148 to receive the reaction reservoir, diluent reservoir, and sample reservoir from the sample transfer unit 148. Furthermore, the reagent holder unit 160 is movable to the reagent transfer device 162 for reagent transfer and to the sample precision transfer unit 152B for sample transfer. In some embodiments, the reagent holder unit 160 moves to the sample transfer unit 148 to remove the diluent reservoir and sample reservoir, and to the incubator transfer unit 170 to remove the reaction reservoir.

[0455] The reagent transfer device 162 is used to transfer reagents from the reagent storage device 164 to the reaction reservoir on the reagent rack unit 160. In some embodiments, the reagent transfer device 162 includes multiple pipettes that can simultaneously perform transfers on different assays to support throughput. In some embodiments, the reagent transfer device 162 is controlled at about 30°C to 40°C by heating. In other embodiments, for example, the reagent transfer device 162 is maintained at about 37°C to ensure consistent binding kinetics of the enzyme reaction.

[0456] Reagent storage device 164 stores reagents. The reagent storage device includes a reagent transfer unit configured to transfer reagent packets to predetermined locations. In some embodiments, reagent storage device 164 may transfer reagent packets from reagent loading device 166 to reagent storage device 164, from reagent storage device 164 to a suction position for suction by reagent suction device 162, from suction position to reagent storage device 164, from suction position to disposal position (if reagents are consumed), from reagent storage device 164 to disposal position (if reagents expire), and from reagent storage device 164 to reagent loading device 166 for unloading reagent packets. In some embodiments, reagent storage device 164 is controlled at approximately 2°C to 15°C by heating. In other embodiments, reagent storage device 164 is maintained at approximately 4°C to 10°C.

[0457] The reagent loading device 166 is used to load one or more reagent packs. Users can load reagent packs into the reagent loading device 166.

[0458] Incubator transfer unit 170 transfers reaction reservoirs to and from incubator 172. In some embodiments, incubator transfer unit 170 transfers one or more aspirated reaction reservoirs from reagent rack unit 160 to incubator 172. Furthermore, incubator transfer unit 170 can transfer one or more reaction reservoirs from incubator 172 to reagent rack unit 160. Incubator transfer unit 170 can also remove read or completed reaction reservoirs from incubator 172.

[0459] Incubator 172 is thermally controlled to maintain a predetermined temperature. In some embodiments, incubator 172 is maintained at approximately 30°C to 40°C. In other embodiments, incubator 172 is maintained at approximately 37°C to ensure, for example, immune and enzymatic reactions. Incubator 172 is used to perform assay incubation, by way of example.

[0460] The reaction reservoir transfer unit 174 transfers reaction reservoirs to and from incubator 172. In some embodiments, the reaction reservoir transfer unit 174 transfers incubated reaction reservoirs from incubator 172 to cleaning wheel 176, transfers assay reaction reservoirs from cleaning wheel 176 to incubator 172, transfers reaction reservoirs containing substrates from cleaning wheel 176 to incubator 172 for substrate incubation or enzyme reaction, transfers cleaned reaction reservoirs from incubator 172 to photometry device 190 after substrate incubation, and transfers read or completed reaction reservoirs from photometry device 190 to incubator 172. Used reaction reservoirs can be transported to a disposal location.

[0461] The cleaning wheel 176 receives and supports the reaction reservoir, enabling the material assessment system 106 to perform various aspects of the diagnostic process. (Reference) Figures 23 to 25 An example of a washing wheel 176 is described and illustrated in more detail. In some embodiments, the washing wheel 176 is a thermal control device for separating bound or free analytes from particles after incubation. In some embodiments, the washing wheel 176 is maintained at about 30°C to 40°C. In other embodiments, the washing wheel 176 is maintained at about 37°C to ensure, for example, enzyme reactions.

[0462] The substrate dispensing device 178 is used to dispense the substrate into a cleaned reaction reservoir. An example of a substrate is a chemiluminescent substrate for immunoassay enzyme reactions, such as Lumi-Phos 530, which generates light to provide detection corresponding to the amount of analyte trapped on magnetic particles.

[0463] The substrate loading device 180 is used to load one or more substrates to be supplied. In some embodiments, the substrate loading device 180 includes a set of two bottles, one in use and the other arranged for unloading and new loading processes. The substrate suction device 178 can be used to aspirate substrate from the bottle in use.

[0464] The light measurement device 190 is used to detect and measure light generated by immunoassay (e.g., Figure 4 The light (L) in the photometer. In some embodiments, the photometer 190 (also referred to as a photometer) includes an opaque package containing a photomultiplier tube (PMT) for reading the amount of chemiluminescence from a reaction reservoir containing a substrate. The reaction reservoir can be transferred to and removed from the photometer 190 by the reaction reservoir transfer unit 174.

[0465] The evaluation processing device 192 is used to receive information about the amount of light detected by the light measurement device 190 and to evaluate and analyze based on that information.

[0466] Figure 3 Exemplary architectures of computing devices that can be used to implement aspects of this disclosure are shown, including the biological specimen analysis instrument 100 or various systems of the instrument 100, such as material preparation system 102, preparation evaluation system 104, and material evaluation system 106. Additionally, one or more devices or units included in the system of instrument 100 can also be used as... Figure 3 The computing device shown is implemented using at least some of its components. This computing device is designated herein by reference numeral 200. The computing device 200 is used to execute the operating system, applications, and software modules (including a software engine) described herein.

[0467] In some embodiments, computing device 200 includes at least one processing device 202, such as a central processing unit (CPU). Various processing devices are available from multiple manufacturers, such as Intel Corporation or Advanced Micro Devices. In this example, computing device 200 also includes system memory 204 and a system bus 206 that couples multiple system components, including system memory 204, to processing device 202. System bus 206 is one of many different types of bus architectures, including a memory bus or memory controller; a peripheral bus; and a local bus using any of a variety of bus architectures.

[0468] Examples of computing devices suitable for computing device 200 include desktop computers, laptop computers, tablet computers, and mobile devices (such as smartphones, etc.). A mobile digital device or other mobile device, or other device configured to process digital instructions.

[0469] System memory 204 includes read-only memory 208 and random access memory 210. A basic input / output system 212 containing basic routines is typically stored in read-only memory 208, which are used to transfer information within computing device 200, such as during startup.

[0470] In some embodiments, the computing device 200 further includes an auxiliary storage device 214, such as a hard disk drive, for storing digital data. The auxiliary storage device 214 is connected to the system bus 206 via an auxiliary storage interface 216. The auxiliary storage device and its associated computer-readable medium provide the computing device 200 with non-volatile storage of computer-readable instructions (including application programs and program modules), data structures, and other data.

[0471] While the exemplary environment described herein uses a hard disk drive as a secondary storage device, other types of computer-readable storage media are used in other embodiments. Examples of these other types of computer-readable storage media include magnetic tape cassettes, flash memory cards, digital video disks, Bernoulli cassettes, optical disc read-only memory, digital universal disk read-only memory, random access memory, or read-only memory. Some embodiments include non-transitory media.

[0472] Several program modules may be stored in auxiliary storage device 214 or memory 204, including operating system 218, one or more application programs 220, other program modules 222 and program data 224.

[0473] In some embodiments, computing device 200 includes input devices to enable a user to provide input to computing device 200. Examples of input devices 226 include keyboard 228, pointer input device 230, microphone 232, and touch-sensitive display 240. Other embodiments include other input devices 226. Input devices are typically connected to processing device 202 via input / output interface 238 coupled to system bus 206. These input devices 226 can be connected via many different input / output interfaces, such as parallel ports, serial ports, game ports, or universal serial buses. Wireless communication between the input device and interface 238 is also possible, and in some possible embodiments, it includes infrared, Wireless technology, WiFi technology (802.11a / b / g / n, etc.), cellular or other radio frequency communication systems.

[0474] In this exemplary embodiment, the touch-sensitive display device 240 is also connected to the system bus 206 via an interface (such as a video adapter 242). The touch-sensitive display device 240 includes touch sensors for receiving input from the user when the user touches the display. These sensors may be capacitive sensors, pressure sensors, or other touch sensors. The sensors detect not only contact with the display but also the location of the contact and its movement over time. For example, the user may move a finger or stylus on the screen to provide write input. The write input is evaluated, and in some embodiments, it is converted into text input.

[0475] In addition to the display device 240, the computing device 200 may include various other peripheral devices (not shown), such as speakers or printers.

[0476] The computing device 200 also includes a communication device 246 configured to establish communication across a network. In some embodiments, when used in a local area network (LAN) or wide area network (WAN) environment, such as the Internet, the computing device 200 is typically connected to a network via a network interface, such as a wireless network interface 248. Other possible embodiments use other wired and / or wireless communication devices. For example, some embodiments of the computing device 200 include an Ethernet network interface or a modem for communication across a network. In other embodiments, the communication device 246 is capable of short-range wireless communication. Short-range wireless communication is unidirectional or bidirectional short- to medium-range wireless communication. Short-range wireless communication can be established according to various technologies and protocols. Examples of short-range wireless communication include radio frequency identification (RFID), near field communication (NFC), Bluetooth, and Wi-Fi.

[0477] Computing device 200 typically includes at least some form of computer-readable medium. Computer-readable medium includes any available medium accessible by computing device 200. For example, computer-readable medium includes computer-readable storage media and computer-readable communication media.

[0478] Computer-readable storage media include volatile and non-volatile, removable and non-removable media implemented in any means for storing information such as computer-readable instructions, data structures, program modules or other data. Computer-readable storage media include, but are not limited to, random access memory, read-only memory, electrically erasable programmable read-only memory, flash memory or other storage technologies, optical disc read-only memory, digital versatile optical disc or other optical storage, magnetic tape cassettes, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible by the computing device 200.

[0479] Computer-readable communication media are generally specifically expressed as computer-readable instructions, data structures, program modules, or other data in modulated data signals (such as carrier waves or other transmission mechanisms), and include any information transmission medium. The term "modulated data signal" refers to a signal having one or more of its characteristics set or altered in a certain way to encode information in the signal. For example, computer-readable communication media include wired media, such as wired networks or direct wired connections; and wireless media, such as voice, radio frequency, infrared, and other wireless media. Any combination of the above is also included within the scope of computer-readable media.

[0480] Blood samples are whole blood, serum, plasma, and other blood components or components. In some embodiments, the biosample analyzer 100 is configured to analyze one or more types of bodily fluid samples. Bodily fluids include blood, urine, saliva, cerebrospinal fluid, amniotic fluid, feces, mucus, cell or tissue extracts, and nucleic acid extracts. Specimens, also referred to as samples, are collected in, but not limited to, donation centers, physician offices, phlebotomist offices, hospitals, clinics, and other medical facilities. The collected bodily fluids and their components are then often processed, tested, and dispensed in or through clinical laboratories, hospitals, blood banks, physician offices, or other medical facilities. In this disclosure, instrument 100 is primarily described as performing immunoassays, which measure the presence or concentration of macromolecules in solution using antibodies or immunoglobulins. Such macromolecules are also referred to herein as analytes. However, in other embodiments, instrument 100 includes any type of biosample analyzer. For example, instrument 100 may be a clinical chemistry analyzer, blood typing analyzer, nucleic acid analyzer, microbiology analyzer, or any other type of in vitro diagnostic (IVD) analyzer.

[0481] Figure 4 This is a schematic diagram illustrating an exemplary method 300 for immunological analysis. In some embodiments, method 300 includes operations 302, 304, 306, 308, 310, 312, and 314. In some embodiments, at least some of the operations in method 300 are performed by the material preparation system 102, the preparation evaluation system 104, and / or the material evaluation system 106 of instrument 100.

[0482] At operation 302, the colorimetric tube 320 (e.g., a reaction reservoir) is transported to a predetermined location, and a first reagent comprising magnetic particles 322 is dispensed into the colorimetric tube 320. In some embodiments, the colorimetric tube 320 is a reaction reservoir and is transported to a cleaning wheel 176.

[0483] At operation 304, the sample or specimen 324 is dispensed into the colorimetric tube 320. In some embodiments, a sample aspiration device 152, engaged with an aspiration tip supplied from the aspiration tip feeder 150, aspirates the sample 324 from a sample reservoir that has been transported to a predetermined location. Once the sample has been dispensed into the colorimetric tube 320, the colorimetric tube 320 can be mixed, if desired, to produce magnetic particle carriers, each magnetic particle carrier being formed by the binding of antigen and magnetic particles from the sample 324.

[0484] At operation 306, a first cleaning process is performed on the colorimetric tube 320, wherein the magnetic particle carrier is magnetically collected by the magnetic collection unit 326 and bound-to-free separated by the bound-to-free cleaning suction nozzle 328. Thus, unreacted material 330 in the colorimetric tube 320 is removed.

[0485] At operation 308, a second reagent 332 (such as a labeling reagent including a labeled antibody) is dispensed into a colorimetric tube 320. This results in the formation of an immune complex 334 consisting of the magnetic particle carrier and the labeled antibody 332 bound together.

[0486] At operation 310, a second binding-free cleaning process is performed to magnetically collect the magnetic particle carrier by the magnetic collection structure 336. Furthermore, binding-free separation is performed by the binding-free cleaning aspiration nozzle 338. Thus, labeled antibody 332 that is not bound to the magnetic particle carrier is removed from the colorimetric tube 320.

[0487] At operation 312, the substrate containing enzyme 340 is dispensed into colorimetric tube 320 and then mixed. After the enzyme reaction has proceeded for the required reaction time, colorimetric tube 320 is transported to a photometric system, such as photometer 190.

[0488] At operation 314, enzyme 340 and immune complex 334 bind together via an enzyme reaction on labeled antibody 332 via substrate 340, and light L is emitted from immune complex 334 and measured by a photometric system (such as photometer 190). Photometer 190 is used to calculate the amount of antigen contained in the specimen based on the amount of light measured.

[0489] See Figures 5 to 39 This describes an example of a volume detection system 120.

[0490] Figure 5 yes Figure 1 A block diagram of an example volume detection system 120. In some embodiments, the volume detection system 120 includes a dispensing tip volume detection device 400 and a reservoir volume detection device 402. The volume detection system 120 also includes a correlation data generation system 404 for generating correlation data 406.

[0491] The dispensing tip volume detection device 400 is used to detect the volume of fluid substance 118 drawn into the dispensing tip 112.

[0492] Fluid substance 118 can be any type suitable for dispensing in a container and presenting for further analysis. In various embodiments, fluid substance 118 can be a specimen to be analyzed, a sample preparation component, a diluent, a buffer, a reagent, or any combination thereof. Where fluid substance 118 involves blood or a component thereof, examples of fluid substance 118 include whole blood, plasma, serum, red blood cells, white blood cells, platelets, diluents, reagents, or any combination thereof. Fluid substance 118 can be other types of bodily fluid substances, such as saliva, cerebrospinal fluid, urine, amniotic fluid, feces, mucus, cell or tissue extracts, nucleic acids, or any other type of bodily fluid, tissue, or material suspected of containing the target analyte. Where fluid substance 118 is a reagent, the reagent can be of various types known for analyzing biological specimens. Some examples of reagents include liquid reagents containing labeled specific binding reagents (e.g., antibodies or nucleic acid probes), liquid reagents containing reactive and / or non-reactive substances, red blood cell suspensions, and particulate suspensions. In other embodiments, the reagent can be a chemiluminescent substrate.

[0493] As described herein, the dispensing tip 112 can be of various types and used in different processes. An example of the dispensing tip 112 is a suction tip that can be used with the sample transfer device 152. The dispensing tip volume detection device 400 can utilize the dispensing tip image capture unit 130. Reference Figures 9 to 21 An example of the dispensing tip volume detection device 400 is illustrated and described in more detail.

[0494] The reservoir volume detection device 402 is used to detect the volume of the fluid substance 118 contained in the reservoir 114. As described herein, the reservoir 114 can be of various types and used in different processes. Examples of reservoirs 114 include reaction reservoirs, sample reservoirs, and diluent reservoirs, which are used throughout the process in instrument 100. The reservoir volume detection device 402 may utilize the reservoir image capture unit 132. (Reference) Figures 22 to 39 An example of the reservoir volume detection device 402 is illustrated and described in more detail.

[0495] The correlation data generation system 404 generates correlation data 406. The correlation data 406 provides information used by the volume detection system 120 to determine the volume of the fluid substance 118 contained in the container 110. In some embodiments, the correlation data generation system 404 is a separate device from the volume detection system 120. In other embodiments, the correlation data generation system 404 is configured to use at least some resources of the volume detection system 120.

[0496] Figure 6 A flowchart illustrating an exemplary method 410 of the operating volume detection system 120 is provided. In some embodiments, at least some operations in method 410 are performed by the material preparation system 102, the preparation evaluation system 104, and / or the material evaluation system 106 of the instrument 100. In other embodiments, other components, units, and devices of the instrument 100 are used to perform at least one operation in method 410.

[0497] At operation 412, fluid substance 118 is provided into container 110. In some embodiments, material preparation system 102 may perform operation 412. In other embodiments, container 110 is preloaded with fluid substance 118 before being loaded into instrument 100 and used by the instrument.

[0498] At operation 414, a container 110 containing fluid substance 118 is transported to an image capture unit, such as a dispensing tip image capture unit 130 and a reservoir image capture unit 132.

[0499] At operation 416, the image capture unit captures an image of container 110. In some embodiments, the image of container 110 is a digital image with a predetermined resolution.

[0500] At operation 418, the evaluation system 104 (e.g., volume detection system 120) is prepared to analyze the image to determine the volume of the fluid substance 118 within container 110. (Refer to...) Figure 7 An example of operation 416 is described in more detail.

[0501] At operation 420, the evaluation system 104 (e.g., volume detection system 120) is prepared to determine whether the determined volume falls within tolerance. When the determined volume is outside the tolerance, it is considered inappropriate to provide fluid substance 118 into container 110. In some embodiments, such a tolerance range is determined based on the allowable deviation from the target volume of fluid substance 118 to be provided into container 110. When it is determined that the detected volume falls within this tolerance range (yes is selected at operation 420), method 410 proceeds to perform the predetermined next step. Otherwise (no is selected at operation 420), method 410 proceeds to operation 422.

[0502] At operation 422, the evaluation system 104 (e.g., volume detection system 120) is prepared to mark container 110 to indicate that the volume of fluid substance 118 within container 110 is unsuitable for subsequent processes. Alternatively, the evaluation system 104 is prepared to stop the relevant testing or analytical process in instrument 100. In other embodiments, the evaluation results can be used to automatically adjust potentially erroneous test results due to an inappropriate volume of fluid substance. In other embodiments, as described herein, the evaluation results can be used to automatically adjust the volume of fluid substance in response to a volume determination.

[0503] Figure 7 It shows the method for execution Figure 6 The flowchart illustrates an exemplary method 430 of operation 418. Specifically, method 430 provides a process for analyzing captured images of container 110 to determine the volume of fluid substance 118 contained in container 110.

[0504] At operation 432, the evaluation system 104 (e.g., volume detection system 120) is prepared to detect reference points in the image. These reference points are associated with container 110. In some embodiments, the reference point includes the location or portion of a detectable structure formed on container 110. In other embodiments, the reference point is configured as part of container 110. Other examples of reference points are also possible. Various image processing methods can be used to detect the surface layer of fluid material 118 in the image.

[0505] At operation 434, the evaluation system 104 (e.g., volume detection system 120) is prepared to detect the surface layer of the fluid substance 118 within the container 110 in the image. Various image processing methods can be used to detect the surface layer of the fluid substance 118 in the image.

[0506] At operation 436, the evaluation system 104 (e.g., volume detection system 120) is prepared to measure the distance between the reference point and the surface layer. In some embodiments, the distance is measured according to the pixel distance between the reference point and the surface layer in the image. In some embodiments, the pixel distance is calculated based on the Euclidean distance between two pixels.

[0507] At operation 438, the evaluation system 104 (e.g., volume detection system 120) is prepared to convert distances to volumes based on correlation data 406. Correlation data 406 includes information about the correlation between volumes within container 110 and distances from a reference point to multiple different surfaces within container 110. (Refer to...) Figure 8 An exemplary method for generating correlation data is described.

[0508] Figure 8This is a flowchart illustrating an exemplary method 450 for operating the correlation data generation system 404 to generate correlation data 406. In some embodiments, at least a portion of the instrument 100 is used as the correlation data generation system 404. In other embodiments, the correlation data generation system 404 generates correlation data independently of the instrument 100.

[0509] At operation 452, the correlation data generation system 404 supplies liquid to the container. The container used in method 450 is the same container 110 that has undergone the volume detection process described herein. The liquid used in method 450 does not need to be the same fluid substance 118 used in instrument 100.

[0510] At operation 454, the correlation data generation system 404 captures an image of a container containing liquid.

[0511] At operation 456, the correlation data generation system 404 extracts the distance between the reference point (i.e., the reference point as described in operation 432) and the fluid surface in the image captured in operation 454. In some embodiments, the distance may be determined by at least some operations similar to those of method 430 (such as operations 432, 434, and 436).

[0512] At operation 458, the correlation data generation system 404 measures the volume of liquid supplied to the container. Various methods can be used to determine the volume of liquid within the container. Some of these methods are described in this document.

[0513] At operation 460, the correlation data generation system 404 correlates the distance calculated at operation 456 with the volume measured at operation 458.

[0514] At operation 462, the correlation data generation system 404 determines whether a sufficient number of correlations have been performed to generate correlation data 406. If so (yes is selected at operation 470), method 450 proceeds to operation 464. Otherwise (no is selected at operation 470), method 450 returns to operation 452, where liquid is supplied to the container, and subsequent operations are performed to determine additional correlations between the distance and the volume of liquid within the container. To obtain a sufficient range of correlation data, the amount of liquid supplied to the container can be varied in different correlation process cycles. Furthermore, for some correlation cycles, the amount of liquid supplied to the container can be kept approximately the same to obtain reliable results for a specific volume or volume range.

[0515] At operation 464, the correlation data generation system 404 creates correlation data 408 based on multiple correlations performed at operation 460. In some implementations, the correlation data 408 can be extrapolated to infer the relationship between distance and volume. For example, correlation curves, lookup tables, or mathematical formulas can be created from the correlation data 408 to fit the data and estimate the relationship between distance and volume within the container.

[0516] See Figures 9 to 21 , described Figure 5 An example of a distribution tip volume detection device 400.

[0517] Figure 9 It shows Figure 5 An example of a dispensing tip volume detection device 400. In some embodiments, the dispensing tip volume detection device 400 includes a sample aspiration volume detection device 500. Furthermore, the dispensing tip volume detection device 400 uses tip volume correlation data 506 generated by a tip volume correlation data generation system 504.

[0518] The sample aspiration volume detection device 500 is used to determine the volume of the sample aspirated into the sample transfer tip of the sample transfer device 152. An example of the structure and operation of the sample aspiration volume detection device 500 is described below.

[0519] Tip volume correlation data generation system 504 generates tip volume correlation data 506. Tip volume correlation data 506 provides information used by dispensing tip volume detection device 400 to determine the volume of fluid material received in the dispensing tip (e.g., sample transfer tip). In some embodiments, tip volume correlation data generation system 504 is a device independent of dispensing tip volume detection device 400. In other embodiments, tip volume correlation data generation system 504 is configured to use at least some resources of dispensing tip volume detection device 400. Tip volume correlation data generation system 504 and tip volume correlation data 506 are included in correlation data generation system 404 and correlation data 406, or are examples of correlation data generation system and correlation data, such as... Figure 5 As shown.

[0520] Reliable clinical diagnosis requires accurate and precise aspiration and dispensing of the substances to be analyzed. For example, in automated analyzers analyzing specimens such as blood or any other bodily fluids, fluctuations in the dispensed volume and other substances, such as reagents in the reaction reservoir, relative to specified amounts can affect analytical results and reduce the reliability of the examination and analysis. Therefore, it is beneficial to develop a technique for measuring aspirated or dispensed volumes with high accuracy and selecting only aspirated or dispensed specimens within appropriate ranges. One method for measuring liquid volume is to detect the liquid surface by using a resonant frequency to determine the height of the liquid within the container. In other cases, air pressure is used to determine the viscosity of the liquid (e.g., the sample) aspirated by the dispensing tip. In still other cases, a flow sensor is used to determine the flow rate of the aspirated or dispensed liquid.

[0521] However, these methods have various drawbacks. For example, using resonant frequency to detect the liquid surface and using air pressure to detect fluid viscosity can determine the volume of liquid in a container, but cannot quantify the volume of liquid being pumped or dispensed. Flow sensors can quantify the volume of liquid passing through a pipe arranged with the flow sensor, but cannot reliably measure the volume of liquid being pumped or dispensed. These methods are not suitable for identifying inaccurate sample pumping processes in the event of erroneous results.

[0522] As described in more detail herein, the dispensing tip volume detection device 400 employs image processing methods to quantify the volume of aspirated fluid material (e.g., a sample). The volume of fluid material is aspirated into a transparent or translucent container (such as a tapered dispensing tip). The container is imaged, and a reference point is detected in the image. The dispensing tip volume detection device measures the distance from the meniscus of the fluid material to the reference point and correlates this distance with the volume using a volume calibration curve. If the volume aspirated within the container does not meet the specifications for aspiration accuracy or precision, the aspiration or the entire test is flagged. The user or operator can receive information about the aspiration results.

[0523] Figure 10 An exemplary structure of a sample aspiration system 510 incorporating a sample aspiration volume detection device 500 is schematically illustrated. In the illustrated example, the sample aspiration volume detection device 500 is primarily described and shown as an example of a dispensing tip volume detection device 400. However, it should be understood that any type of dispensing tip volume detection device 400 can be used in the same or similar manner as the sample aspiration volume detection device 500.

[0524] In some embodiments, the sample aspiration system 510 includes a sample aspiration module 512 movable between different locations along a sample transfer guide 514. The sample aspiration module 512 is movable to a tip supply position 516, a sample dispensing position 518, a tip discard position 520, and a sample aspiration position 522. In some embodiments, the sample aspiration module 512 includes a base 524 and a mandrel 526 supported on the base 524. The sample aspiration module 512 includes a vertical transfer unit 528 configured to vertically move the base 524, including the mandrel 526, relative to the sample container 530. The mandrel 526 is configured to mount a dispensing tip 112, which is also referred herein as an aspiration tip or probe, an aspiration tip or probe, or a disposable tip or probe.

[0525] On instrument 100, a sample is aspirated from the dispensing tip to avoid the risk of contamination. The sample aspiration module 512 is movable to tip supply position 516 and its base 524 is vertically lowered to insert a mandrel 526 into the dispensing tip 112 supplied by the dispensing tip supply unit 534. The sample aspiration module 512 then moves to sample aspiration position 522, where it aspirates a predetermined volume of sample 540 from the sample container 530. Once the sample is aspirated, the sample aspiration volume detection device 500 detects the volume of sample aspirated from the dispensing tip 112. In some embodiments, the sample aspiration volume detection device 500 includes a dispensing tip image capture unit 130 to capture an image of the dispensing tip 112 during volume detection. Afterward, the sample aspiration module 512 moves to sample dispensing position 518 to dispense the aspirated sample volume into the reaction container 536, and then moves to tip discarding position 520 to discard the dispensing tip 112 into the dispensing tip discarding unit 538.

[0526] In some implementations, the sample aspiration system 510 is implemented using at least some components of the instrument 100, such as... Figure 2 As shown. For example, sample transfer module 512 corresponds to sample transfer device 152 of instrument 100 (including sample aliquot transfer unit 152A and sample precision transfer unit 152B). Sample container 530 may correspond to sample tube. Dispensing tip supply unit 534 may correspond to transfer tip feeder 150. Reaction container 536 may correspond to sample reservoir, reaction reservoir or any other reservoir.

[0527] Figure 11 , 12A And 12B shows Figure 10 The sample suction system 510. Figure 11 yes Figure 10 A perspective view of the sample aspiration system. Figure 12A This is a side view of the sample aspiration system 510. Figure 12B This is another side view of the sample aspiration system 510, showing the sample aspiration module 512 in the sample aspiration position 522 for volume detection using the sample aspiration volume detection device 500.

[0528] As shown in the figure, the dispensing tip image capture unit 130 includes a first camera unit 550 and its associated components, which are mounted to the sample dispensing and transfer unit 152A. In some embodiments, the first camera unit 550 and these other components are configured to move together with the corresponding mandrel and dispensing tip of the sample dispensing and transfer unit 152A.

[0529] In some embodiments, camera unit 550 includes a complementary metal-oxide-semiconductor (CMOS) image sensor for acquiring color digital images. In other embodiments, camera unit 550 includes a charge-coupled device (CCD) image sensor for acquiring color digital images. As shown in FIG12, camera unit 550 is located on one side of the dispensing tip 112. Other embodiments of camera unit 550 are configured to acquire black-and-white or grayscale images. An example of camera unit 550 includes a model named ADVANTAGE 102, obtained from Cognex Corporation (Nartick, MA), such as the AE3-IS machine vision color camera + IO board (e.g., part number AE3C-IS-CQBCKFS1-B).

[0530] The distribution tip image capture unit 130 may also include a light source 552 for the camera 550. The light source 552 is used to illuminate the distribution tip 112 to be photographed and its surroundings as needed. The light source 552 can be arranged in various locations. In the example shown, the light source 552 is positioned behind the distribution tip 112, opposite the camera unit 550, and thus serves as a backlight. Other locations for the light source 552 are also possible. An example of the light source 552 includes the MDBL series purchased from Moritex Corporation (Japan).

[0531] In other embodiments, camera unit 550 includes a light source 551, such as an LED, operable to emit light toward distribution tip 112. In this configuration, light source 552 may be replaced by screen 553, arranged opposite camera unit 550 such that distribution tip 112 is positioned between camera unit 550 and screen 553. Screen 553 is used to project light in the direction of the camera unit's field of view (FOV) by reflecting light toward the camera's aperture. Screen 553 is made of one or more materials that can provide different intensities of reflection. For example, screen 553 includes a retroreflective sheet, one example of which includes 3M products purchased from 3M Corporation (Maplewood, Minnesota). TM ScotchliteTM Sheet 7610 (3M) TM Scotchlite TM (Sheeting 7610). In other embodiments, the light source 552 may be used in conjunction with the light source 551 and the screen 553 from the camera unit 550.

[0532] In some embodiments, camera unit 550 and light source 552 (or screen 553) are attached to sample transfer module 512 and configured to move horizontally with sample transfer module 512, such that an image of dispensing tip 112 is captured at any location on sample transfer module 512. For example, an image of dispensing tip 112 containing aspirated sample can be acquired at any location before sample aspiration (i.e., sample aspiration position 522) and before sample dispensing (i.e., sample dispensing position 518). In other embodiments, camera unit 550 is attached to sample transfer module 512, while light source 552 (or screen 553) is not attached to sample transfer module 512. In another embodiment, camera unit 550 is not attached to sample transfer module 512, while light source 552 (or screen 553) is attached to sample transfer module 512. In other embodiments, neither camera unit 550 nor light source 552 (or screen 553) is attached to sample transfer module 512.

[0533] Furthermore, the tip image capture unit 130 may include a second camera unit 2550 and its associated components, which are mounted to the sample precision aspiration unit 152B. The second camera unit 2550 and its associated components may be configured similarly to the first camera unit 550 and its associated components.

[0534] In some implementations, the second camera unit 2550 and these other components are configured to move together with the corresponding mandrel and dispensing tip of the sample dispensing unit 152A.

[0535] The second camera unit 2550 can be configured to be similar to the first camera unit 550. An example of the camera unit 2550 includes a model called ADVANTAGE 102, which is derived from Cognex Corporation (Nartick, MA), such as the AE3-IS machine vision camera + IO board (e.g., part number AE3-IS-CQBCKFP2-B).

[0536] The distribution tip image capture unit 130 may also include a light source 2552 for the camera 2550. The light source 2552 is used to illuminate the distribution tip 112 to be photographed and its surroundings as needed. The light source 2552 can be arranged in various locations. In the example shown, the light source 2552 is positioned behind the distribution tip 112, opposite the camera unit 2550, and thus serves as a backlight. Other locations for the light source 2552 are also possible. An example of the light source 2552 includes the MDBL series purchased from Moritex Corporation (Japan).

[0537] In other embodiments, camera unit 550 includes a light source 2551, such as an LED, operable to emit light toward distribution tip 112. In this configuration, light source 2552 may be replaced by screen 2553 arranged opposite camera unit 550 such that distribution tip 112 is positioned between camera unit 2550 and screen 2553. Screen 2553 is used to project light in the direction of the camera unit's field of view (FOV) by reflecting light toward the camera's aperture. Screen 2553 is made of one or more materials that can provide different intensities of reflection. For example, screen 2553 includes a retroreflective sheet, one example of which includes 3M products purchased from 3M Corporation (Maplewood, Minnesota). TM Scotchlite TM Sheet 7610 (3M) TM Scotchlite TM (Sheeting 7610). In other embodiments, the light source 2552 may be used in conjunction with the light source 2551 and the screen 2553 from the camera unit 2550.

[0538] In some embodiments, the camera unit 2550 and the light source 2552 (or screen 2553) are configured to be fixed and independent of the movement of the sample suction module 512. In other embodiments, other configurations are also possible.

[0539] As described in this article, camera unit 2550 and its related components can be used for tip alignment detection, such as Figure 67 As further shown in the text.

[0540] See Figure 13 and 14 This describes an example of the allocation of tip 112. Specifically, Figure 13 This is a schematic perspective view of an example of the allocation of tip 112. Figure 14 It is a cross-sectional view of the distal end of the tip 112.

[0541] Dispensing tip 112 extends from a proximal end 560 and a distal end 562. Dispensing tip 112 includes a base portion 564 at the proximal end 560, configured to attach dispensing tip 112 to a mandrel 526 of sample aspiration module 512. Dispensing tip 112 also includes an elongated body portion 566 extending from the base portion 564. Dispensing tip 112, including the base portion 564 and the body portion 566, defines an aspiration channel (or channel) 572 for aspirating, containing, and dispensing fluid material. In some embodiments, dispensing tip 112 (including dispensing tip 112) is disposable. In other embodiments, dispensing tip 112 (including dispensing tip 112) is a non-disposable or multiple pieces available before disposal.

[0542] In some embodiments, the dispensing tip 112 includes a reference line 570 detectable by the dispensing tip image capture unit 130. The reference line 570 may be formed at various locations on the dispensing tip 112. In some embodiments, the reference line 570 is formed on the body portion 566 of the dispensing tip 112. In other embodiments, the reference line 570 is formed on the base portion 564 of the dispensing tip 112. Some examples of the reference line 570 are positioned such that the surface or meniscus of the fluid material drawn into the dispensing tip 112 is disposed between the reference line 570 and the distal end 562 of the dispensing tip 112. In other embodiments, the reference line 570 is positioned such that the meniscus of the fluid material drawn into the dispensing tip 112 is disposed above the reference line 570 relative to the distal end 562 (i.e., between the reference line 570 and the proximal end 560).

[0543] Reference lines 570 are provided to the dispensing tip 112 in various ways. In some embodiments, reference lines 570 are detectable structures, such as protrusions, ridges, recesses, notches, or any other visible elements formed on the dispensing tip 112. In other embodiments, reference lines 570 are marks or indicators applied or attached to the dispensing tip 112. Reference lines 570 may be integrally formed or molded to the dispensing tip 112. Alternatively, reference lines 570 may be manufactured separately and attached to the dispensing tip 112.

[0544] Reference line 570 serves as a reference point when analyzing an image of the dispensing tip 112 to determine whether the sample has been properly aspirated for analytical testing. As described herein, the sample aspiration volume detection device 500 measures the volume of sample aspirated into the dispensing tip 112 by measuring the distance between reference line 570 and the sample meniscus. Because reference line 570 is formed on the dispensing tip 112, it provides a consistent reference point for volume measurement compared to any reference point provided by other structures besides the dispensing tip 112. For example, if a portion or point in the mandrel 526 is used as a reference point, the position of the mandrel 526 relative to the dispensing tip 112 can vary depending on the insertion depth from the dispensing tip 112 to the mandrel 526, resulting in inaccurate volume measurements. In contrast, reference line 570 is fixed relative to the dispensing tip 112, thus providing accurate measurements.

[0545] like Figure 14 As shown, the aspiration channel 572 includes a tapered portion 574, wherein the inner diameter decreases from the proximal end 560 to the distal end 562. The aspiration channel 572 also includes a straight portion 576, which has a constant inner diameter at or near the distal end 562. The straight portion 576 can improve the accuracy and precision of aspirating small volumes (such as about 2 to 5 μL) while still providing a dispensing tip 112 for aspirating large volumes (such as 250 μL) for equal dispensing.

[0546] Figure 15 This is a flowchart illustrating an exemplary method 600 for operating a dispensing tip volume detection device 400. In the illustrated example, method 600 is described primarily with respect to a sample aspiration volume detection device 500. However, method 600 is similarly applicable to other types of dispensing tip volume detection devices 400. In some embodiments, method 600 is performed by a sample aspiration system 510 and a sample aspiration volume detection device 500.

[0547] Generally, Method 600 uses a metrological algorithm to perform an analysis of the volume of suction drawn into the dispensing tip, and if the calculated suction volume is outside the tolerance range, the suction result or test result is marked.

[0548] At operation 602, the sample aspiration system 510 is used to aspirate fluid substances (such as sample 540) according to the design. Figure 10 )) Aspirate into the dispensing tip 112.

[0549] At operation 604, the sample aspiration system 510 transports the dispensing tip 112, containing the sample 540 aspirated, to the dispensing tip image capture unit 130. In some embodiments, the dispensing tip image capture unit 130 is arranged to capture an image of the dispensing tip 112 after aspiration without transport.

[0550] At operation 606, the dispensing tip image capture unit 130 of the sample aspiration volume detection device 500 captures an image of the dispensing tip 112. In some embodiments, the image of the dispensing tip 112 is a digital image of a predetermined resolution.

[0551] At operation 608, the sample aspiration volume detection device 500 analyzes the image to determine the volume of sample 540 within the dispensing tip 112. (Refer to...) Figures 16 to 19 An example of operation 608 is described in more detail.

[0552] At operation 610, the sample aspiration volume detection device 500 determines whether the determined volume falls within a tolerance range. When the determined volume is outside the tolerance range, aspiration of sample 540 into dispensing tip 112 is considered inappropriate. In some embodiments, such a tolerance range is determined based on an allowable deviation from the target aspiration volume of sample 540, which is expected to be aspirated into dispensing tip 112. This tolerance range may vary depending on the target aspiration volume. An example of a tolerance range is as follows:

[0553] Table 1

[0554] Target aspiration volume (V) Tolerance range 2μL≤V<10μL 100±30％ 10μL≤V<50μL 100±15％ 50μL≤V<110μL 100±10％

[0555] When it is determined that the detected volume falls within the tolerance range ("Yes" is selected at operation 610), method 600 proceeds to the next predetermined step. Otherwise ("No" is selected at operation 610), method 600 proceeds to operation 612.

[0556] At operation 612, the sample aspiration volume detection device 500 marks the aspiration to indicate that the sample volume aspirated in the dispensing tip 112 is unsuitable for subsequent processes. In other embodiments, the entire test result using the aspirated sample may be marked to indicate or suggest that the test result may be incorrect. Alternatively, the sample aspiration volume detection device 500 is used to stop an associated test or analysis process in instrument 100. In other embodiments, the evaluation results can be used to automatically adjust for potentially erroneous test results due to inappropriate volumes of fluid substances. In other embodiments, as described herein, the evaluation results can be used to automatically adjust the volume of the fluid substance in response to a volume determination.

[0557] See Figures 16 to 19 , described Figure 15 An example of operation 608, in which the captured image is analyzed to determine the sample volume in the dispensing tip. Specifically, Figure 16 It shows the method for execution Figure 15 A flowchart of an exemplary method 630 for operation 608. Also refer to... Figures 17 to 19Method 630 is described, and these figures illustrate exemplary analysis of the captured image 620 of the dispensing tip.

[0558] At operation 632, the sample aspiration volume detection device 500 detects the reference line 570 of the distribution tip 112 in the captured image 620. Various image processing methods can be used to detect the reference line 570 in image 620. In some embodiments, the reference line 570 is detected by a pattern matching function that searches for patterns representing the reference line based on a pre-trained reference image. For example, such a pattern matching function performs a pattern search that scans the captured image to look for patterns already stored in the system and identified as reference lines. The correlation value or matching rate (e.g., % match) is adjustable. In other embodiments, other methods are also possible. An example of such image processing methods can be implemented using Cognex In-Sight Vision software, available from Cognex Corporation (Nartick, MA), which offers various tools such as edge detection (“Edge”), pattern matching (“Pattern Match”), and histogram analysis (“Histogram”).

[0559] At operation point 634, the center point 650 of the reference line 570 of the sample aspiration volume detection device 500 is detected. For example... Figure 17 As shown, once reference line 570 is detected, center point 650 can be calculated as the midpoint of reference line 570.

[0560] At operation 636, the sample aspiration volume detection device 500 detects the surface layer 652 (where the sample volume is aspirated) in the dispensing tip 112. Figure 18 Various image processing methods can be used to detect the surface layer 652 in an image. In some implementations, similar to operation 632, the surface layer 652 is detected by a pattern matching function based on a pre-trained reference image. In other implementations, other methods are also possible.

[0561] At operation 638, the sample aspiration volume detection device 500 detects the center point 654 of the surface layer 652. For example... Figure 18 As shown, once surface 652 is detected, center point 654 can be calculated as the midpoint of the straight line of surface 652.

[0562] At operation 640, the distance L1 between the center point 650 of the reference line 570 of the sample aspiration volume detection device 500 and the center point 654 of the surface 652 is ( Figure 19 In some implementations, distance L1 is measured as the pixel distance between center points 650 and 654 in image 620. In some implementations, the pixel distance is calculated based on the Euclidean distance between the two pixels.

[0563] At operation 642, the sample aspiration volume detection device 500 converts distance L1 into volume based on tip volume correlation data 506. The correlation data 506 includes information about the correlation between the volume within the dispensing tip 112 and the distance L1 between the center point 650 of the reference line 570 and the center points 654 of multiple different surfaces 652 within the dispensing tip 112. In some embodiments, the correlation data 506 may be plotted onto a correlation curve 660, such as... Figure 20 As shown. (Refer to...) Figure 21 An exemplary method for generating correlation data 506 is described.

[0564] Figure 20 This is an exemplary correlation curve 660 corresponding to the correlation data 506. In some embodiments, the correlation curve 660 shows the relationship between the distance L1 (e.g., pixel distance) between center points 650 and 654 and the aspiration sample volume V1 in the dispensing tip 112. The correlation curve 660 can be obtained by plotting multiple discrete data points included in the correlation data 506, which will reference... Figure 21 Describe it. For example... Figure 20 As shown, the correlation curve indicates that the aspirated volume V1 typically decreases as the distance L1 increases. Since the reference line 570 is formed on the distribution tip 112 to be positioned above the surface layer 652, the distance L1 is generally negatively correlated with the volume V1.

[0565] Figure 21 This is a flowchart illustrating an exemplary method 670 for operating a tip volume correlation data generation system 504 to generate tip volume correlation data 506.

[0566] In some implementations, spectroscopic techniques are used to create correlation data 506. For example, the tip volume correlation data generation system 504 uses a dye solution to display the correlation between extracted pixel distance information and fluid volume information in the dispensing tip. A spectrophotometer can be used to measure the absorbance of the dye at a specific wavelength. In some implementations, the tip volume correlation data generation system 504 selects multiple points within a target volume range (e.g., 5, 10, 50, 100, and 110 μL), extracts these volume settings by the dispensing tip, and captures an image of the dispensing tip to perform pixel distance calculations. The tip volume correlation data generation system 504 then plots a calibration curve between the pixel distance calculated from the image and the volume calculated by the spectrophotometer.

[0567] At operation 672, the tip volume correlation data generation system 504 draws the dye solution into the distribution tip 112.

[0568] At operation 674, the tip volume correlation data generation system 504 captures an image of the dispensing tip 112 containing the dye solution.

[0569] At operation 676, the tip volume correlation data generation system 504 extracts the distance between reference line 570 and the water surface line of the dye solution in the image captured in operation 674. In some embodiments, the distance is measured as pixel distance. In some embodiments, this distance is determined similarly to at least some operations of method 630 (such as operations 632, 634, 636, 638, and 640). In other embodiments, other methods are also possible.

[0570] During operations 678, 680, and 682, the tip volume correlation data generation system 504 measures the volume of dye solution drawn into the dispensing tip 112. Various methods can be used to determine the volume of the dye solution. In the illustrated example, a spectroscopic method is used, as described below.

[0571] At operation 678, the tip volume correlation data generation system 504 dispenses the dye solution into an auxiliary container with a known volume of diluent.

[0572] At operation 680, the tip volume correlation data generation system 504 measures the optical density of the diluted dye solution dispensed in the auxiliary container. In some embodiments, a spectrophotometer is used to measure the optical density of the dye solution. The spectrophotometer measures the amount of light at a specific wavelength passing through the diluted dye solution in the auxiliary container.

[0573] At operation 682, the tip volume correlation data generation system 504 converts the optical density into the volume of the dye solution in the dispensing tip.

[0574] At operation 684, the tip volume correlation data generation system 504 correlates the distance calculated at operation 676 with the volume obtained at operation 682.

[0575] At operation 686, the tip volume correlation data generation system 504 determines whether a sufficient number of correlations have been performed to generate tip volume correlation data 506. If so (yes is selected at operation 686), method 670 proceeds to operation 688. Otherwise (no is selected at operation 686), method 670 returns to operation 672, in which the dye solution is aspirated into the dispensing tip 112, and subsequent operations are performed to determine additional correlations between distance and the volume of dye solution within the dispensing tip. To obtain a sufficient range of correlation data, different amounts of dye solution are aspirated into the dispensing tip 112 in different correlation cycles. Furthermore, for some correlation cycles, the amount of dye solution aspirated into the dispensing tip can be kept substantially the same to obtain reliable results for a specific volume or volume range.

[0576] At operation 688, the tip volume correlation data generation system 504 creates tip volume correlation data 506 based on multiple correlations performed at operation 684. In some embodiments, the correlation data is presented as a correlation curve (e.g., by plotting the pixel distance of each image against the corresponding aspirated volume measured by a spectrophotometer). Figure 20 The correlation curve (660) is used to estimate the relationship between distance and volume in the distribution tip 112.

[0577] As per reference Figures 9 to 21 The described embodiments can be modified to suit various applications. In some embodiments, the dispensing tip volume detection device 400 is used for any fluid substance other than a patient sample. In some embodiments, the dispensing tip image capture unit of the dispensing tip volume detection device 400 does not use a backlight setup. Furthermore, unlike a set of cameras and backlights that move with the sample transfer module and other associated devices, the dispensing tip image capture unit can utilize a fixed camera and backlight setup. The reference line for the dispensing tip can be any line other than the line formed on the dispensing tip. In some embodiments, the mandrel used for the dispensing tip serves as a reference point. In some embodiments, the pattern matching function associated with the dispensing tip volume detection device 400 employs various algorithms, such as finding straight lines or line segments. In some embodiments, the measurement volume range can be greater than 110 μL. In some embodiments, the dispensing tip volume detection device 400 is used for any container of various shapes (e.g., cylindrical, conical, rectangular, and square) other than the sample transfer tip as shown herein. In other embodiments, the tip volume correlation data generation system 504 uses any liquid other than a dye solution and uses techniques other than spectroscopy. For example, a JIG tip with multiple reference lines corresponding to a known volume can be used.

[0578] An example of the image processing method used above can be implemented using Cognex In-Sight Vision software, which is available from Cognex Corporation (Nartick, Massachusetts) and offers a variety of tools such as edge detection (“Edge”), pattern matching (“Pattern Match”), and histogram analysis (“Histogram”).

[0579] In some implementations, the measured volume of aspirated sample can be used to adjust the relative optical units (RLU) of the test results. Since the sample volume (as well as the substrate / reagent volume, etc.) is correlated with the RLU used for the immunoassay, this correlation can be measured and used as a basis for adjustment. Furthermore, the measured volume can be used as feedback to adjust the reagent volume, thereby improving ratio matching and assay performance.

[0580] See Figures 22 to 39 , described Figure 5 An example of a reservoir volume detection device 402.

[0581] Figure 22 It shows Figure 5 An example of a reservoir volume detection device 402. In some embodiments, the reservoir volume detection device 402 includes a reaction reservoir dispensing volume detection device 700, a reaction reservoir remaining volume detection device 702, a dispensing adjustment device 704, and a reaction reservoir detection device 706. The reaction reservoir dispensing volume detection device 700 uses reservoir volume correlation data 712 generated by the reservoir volume correlation data generation system 710.

[0582] The reaction reservoir dispensing volume detection device 700 is used to determine the volume of fluid substance 118 dispensed into a reservoir 114 (such as a reaction reservoir). Reference Figures 27 to 31 An example of the structure and operation of a reaction reservoir dispensing volume detection device 700 is described and illustrated.

[0583] The reaction reservoir remaining volume detection device 702 is used to determine the volume of fluid substance 118 retained in the reservoir 114 (such as a reaction reservoir). Reference Figures 32 to 34 An example of a reaction reservoir remaining volume detection device 702 is described and illustrated.

[0584] The distribution adjustment device 704 is used to adjust the operation of a material distribution device (such as a suction pump and a dispensing device) based on a measurement of the volume of fluid material distributed to the reservoir 114 (such as a reaction reservoir). See reference. Figure 35 and Figure 36 An example of the allocation adjustment device 704 is described and illustrated.

[0585] The reaction reservoir detection device 706 is used to detect the presence or absence of a reservoir 114 (such as a reaction reservoir). (See reference) Figures 37 to 39 An example of a reaction reservoir detection device 706 is described and illustrated.

[0586] The reservoir volume correlation data generation system 710 generates reservoir volume correlation data 712. Reservoir volume correlation data 712 provides information used by the reservoir volume detection device 402 to determine the volume of fluid substance dispensed into a reservoir (e.g., a reaction reservoir). In some embodiments, the reservoir volume correlation data generation system 710 is a device independent of the reservoir volume detection device 402. In other embodiments, the reservoir volume correlation data generation system 710 is configured to use at least some resources of the reservoir volume detection device 402. The reservoir volume correlation data generation system 710 and the reservoir volume correlation data 712 are included in correlation data generation systems 404 and 406, or are examples of correlation data generation systems and correlation data, such as... Figure 5 As shown.

[0587] After turning Figures 23 to 26 Previously, it should be noted that reliable clinical diagnostics require accurate and precise aspiration and dispensing of the substances to be analyzed. For example, in automated analyzers analyzing specimens such as blood or any other type of bodily fluid, fluctuations in the amount of sample dispensed or aspirated in the container (e.g., aspiration tip or reaction container) and other substances (such as reagents) relative to specified amounts can affect analytical results and reduce the reliability of examination and analysis. Furthermore, in the clinical diagnostics industry, it is difficult to accurately and precisely control and match the volumes of fluid dispensed from different pump units. Therefore, it is beneficial to develop a technique for measuring aspirated or dispensed volumes with high accuracy and selecting only aspirated or dispensed specimens within appropriate ranges. One method for measuring liquid volume is to monitor the fluid pressure in the fluid line and correlate the fluid pressure with the dispensed volume. In other cases, flow sensors are used to determine the flow rate of the aspirated or dispensed liquid. In still other cases, the chemiluminescent signal generated by controlled dispensing of IA reagents is used to determine the presence of excess residual volume in the container after aspiration from the reservoir. In yet another case, the chemiluminescent signal generated by controlled dispensing of IA reagents is used to determine the volume dispensing characteristics of multiple pump units.

[0588] However, these methods have several drawbacks. For example, pressure sensors can determine fluid viscosity but cannot quantify the volume dispensed. Flow sensors can quantify the volume of liquid passing through a pipe arranged by the flow sensor but cannot reliably measure the volume of liquid aspirated or dispensed. Furthermore, due to positional offsets, it is difficult to correlate low-volume measurement continuity with a specific reaction reservoir. Additionally, chemiluminescence signals cannot detect small amounts of residual fluid after aspiration. Chemiluminescence signals cannot provide accurate, direct estimates of volume matching characteristics between different pump units. Chemiluminescence signals can confound reagent properties and batch variations with system variables of interest, such as dispensed or residual volumes.

[0589] As described in more detail herein, the reservoir volume detection device 402 employs image processing methods to quantify the volume of fluid material dispensed and aspirated in a reservoir (e.g., a reaction reservoir). The volume of fluid material dispensed or aspirated is in a transparent or semi-transparent container (such as a transparent cylindrical reservoir). The reservoir is imaged, and a reference point is detected in the image. In some embodiments, a feature at the bottom of the reservoir is used as a reference point within the image. The reservoir volume detection device measures the distance from the meniscus of the fluid material to the reference point and correlates this distance with the volume using a volume calibration curve. If the volume dispensed within the container does not meet the specifications for dispensing accuracy, the dispensing or the entire test is flagged. The user or operator can receive information about the dispensing results.

[0590] In addition, the measured volume of fluid material distributed in the container is recorded according to different combinations of pumps and suction pumps in the system, and this is used to calibrate the combination of pumps and suction pumps to improve the control accuracy of different pumps and suction pumps in the system.

[0591] Furthermore, the container volume detection device 402 can detect the presence of very small amounts of residual fluid material remaining in the container after aspiration. In some embodiments, a pattern recognition algorithm is used for this residual volume detection.

[0592] See Figures 23 to 26 An exemplary structure and operation of a container rack assembly 720, including a container volume detection device 402, are described.

[0593] Figure 23 An exemplary container holder assembly 720 is shown, in which a container volume detection device 402 is included. In the illustrated example, the container holder assembly 720 is implemented in the instrument 100 as a cleaning wheel, such as a cleaning wheel 176. Figure 2 Therefore, the container rack assembly 720 is also referred to herein as a cleaning wheel 720. In these embodiments, other types of container rack assemblies 720 are used in conjunction with the container volume detection device 402.

[0594] As shown in the figure, the container carrier assembly or cleaning wheel 720 is configured to perform various aspects of the diagnostic process. In some embodiments, the cleaning wheel 720 includes a housing unit 722 and a rotatable plate 724 relative to the housing unit 722. The cleaning wheel 720 includes a plurality of container seats 726 formed in the rotatable plate 724 and configured to receive and support containers 728. When the container carrier assembly 720 is configured as a cleaning wheel, these containers 728 include reaction reservoirs. Therefore, the containers 728 are also referred to herein as reaction reservoirs 728.

[0595] In some embodiments, the reservoir volume detection device 402 is mounted to the washing wheel 720. As described above, the reservoir volume detection device 402 includes a reservoir image capture unit 132. (Reference) Figure 24 and 25 An exemplary structure of the storage image capture unit 132 is described in more detail.

[0596] See Figure 24 and 25 An exemplary structure of a reservoir volume detection device 402, including a reservoir image capture unit 132, is described. Specifically, Figure 24 yes Figure 23 Another perspective view of the container holder assembly 720 shows the container image capture unit 132. Figure 25 This is a top view of the cleaning wheel 720, in which the reservoir volume detection device 402 includes a reservoir image capture unit 132.

[0597] The storage image capture device 132 includes a camera unit 730 and a light source 732. In some embodiments, the camera unit 730 includes a complementary metal-oxide-semiconductor (CMOS) image sensor for acquiring color digital images. In other embodiments, the camera unit 730 includes a charge-coupled device (CCD) image sensor for acquiring color digital images. Other embodiments of the camera unit 730 are configured to acquire black-and-white or grayscale images. The light source 732 is used to illuminate the storage container 728, the slot 736, and / or the surrounding environment of the storage container 728 and / or the slot 736, which will be photographed as needed. The light source 732 can be fixed in various locations. In the example shown, the light source 732 is positioned on the back of the storage container 728, facing the camera unit 730, and thus serves as a backlight. Other locations for the light source 732 are also possible. An example of the light source 732 includes the MDBL series purchased from Moritex Corporation (Japan).

[0598] In other embodiments, camera unit 730 includes a light source 731, such as an LED, operable to emit light toward reservoir 728. In this configuration, light source 732 may be replaced by screen 733, arranged opposite camera unit 730 such that reservoir 728 is positioned between camera unit 730 and screen 733. Screen 733 is used to project light in the direction of the camera unit's field of view (FOV) by reflecting light toward the camera's aperture. Screen 733 is made of one or more materials that can provide different intensities of reflection. For example, screen 733 includes a retroreflective sheet, one example of which includes 3M [material name missing] purchased from 3M Company (Maplewood, Minnesota). TM Scotchlite TM Sheet 7610 (3M) TM Scotchlite TM Sheeting 7610). In other embodiments, the light source 732 may be used in conjunction with the light source 731 and screen 733 from the camera unit 730. An example of the camera unit 730 includes a model called ADVANTAGE 102, which is available from Cognex Corporation (Nartick, Massachusetts).

[0599] In some embodiments, the camera unit 730 and the light source 732 (or screen 733) are attached to the housing unit 722 of the cleaning wheel 720. The camera unit 730 and the light source 732 (or screen 733) are arranged such that when the rotatable plate 724 rotates relative to the housing unit 722, the reaction reservoir 728 supported by the rotatable plate 724 is positioned between the camera unit 730 and the light source 732 (or screen 733).

[0600] In some embodiments, housing unit 722 defines a slot 736 that exposes one of the reaction reservoirs 728 between camera unit 730 and light source 732 (or screen 733). When reaction reservoir 728 is aligned with camera unit 730 and light source 732 (or screen 733) through slot 736 of housing unit 722, an image of reaction reservoir 728 can be captured by camera unit 730. In other embodiments, where housing unit 722 is made of an opaque material, housing unit 722 includes a transparent or translucent area replacing slot 736. This transparent or translucent area allows camera unit 730 to capture images through this area.

[0601] An example of camera unit 730 is the ADV102 machine vision camera, such as part number ADV102-CQBCKFW1-B, which was purchased from Cognex Corporation (Nattick, Massachusetts).

[0602] As described above, patient samples contained in reaction reservoirs are transported between various modules, units, or devices within instrument 100. Various aspects of the diagnostic process within instrument 100 are performed in a cleaning wheel 720. The cleaning wheel 720 transports multiple reaction reservoirs 728 around itself. The reaction reservoirs 728 on the cleaning wheel 720 can correspond to multiple test results. In this configuration, a camera unit 730 and a light source 732 (or screen 733) are fixed to the cleaning wheel 720. The camera unit 730 faces the location of the light source 732 (or screen 733) within the cleaning wheel 720. The camera unit 730 captures images of the reaction reservoirs 728 moving through the field of view (FOV) of the camera unit 730 between the camera unit 730 and the light source 732 (or screen 733). In some embodiments, the reaction reservoir 728 becomes stationary while an image of the reaction reservoir 728 is captured by the camera unit 730. In other embodiments, the camera unit 730 captures images of the reaction reservoir 728 as it moves. Images of each reaction reservoir 728 can be captured. The camera unit 730 captures images in multiple steps throughout the diagnostic process as the rotatable plate 724 rotates relative to the housing unit 722. In some embodiments, when the diagnostic process is not in progress, the reaction reservoir can be moved to a position between the camera unit 730 and the light source 732 (or screen 733) (e.g., the container seat 726 located at the slot 736).

[0603] The cleaning wheel 720 can operate in different operating modes. In some embodiments, the cleaning wheel 720 operates in a test processing mode or a diagnostic routine mode. In other embodiments, the cleaning wheel 720 can operate in a test preparation mode, such as filling. In the test processing mode, the cleaning wheel 720 holds one or more reservoirs on a rotatable plate 724 and rotates the reservoirs for a predetermined analytical test. In the diagnostic routine mode (also referred to herein as Automated System Diagnostics (ASD)), the instrument 100 is idle and no tests are run. In some embodiments, in the diagnostic routine mode, the cleaning wheel 720 is operated to perform at least one of the operations for preparing the evaluation system 104, such as reservoir dispensing volume detection (e.g., performed by reaction reservoir dispensing volume detection device 700), reservoir remaining volume detection (e.g., performed by reaction reservoir remaining volume detection device 702), dispensing adjustment (e.g., performed by dispensing adjustment device 704), and reservoir detection (e.g., performed by reaction reservoir detection device 706). In other embodiments, the operations for preparing the evaluation system 104 can be performed in the test processing mode.

[0604] In some implementations, the cleaning wheel 720 operates using multiple dispensing tips, which may have different profiles and accuracies based on their hydraulic characteristics. In test treatment mode, two or more of the dispensing tips can dispense material into reservoirs on the cleaning wheel 720. In diagnostic routine mode, the dispensing tips can operate independently, thus allowing the operational status of each dispensing tip to be monitored and evaluated, such as during dispensing adjustments performed by, for example, the dispensing adjustment device 704.

[0605] Figure 26 This is a flowchart illustrating an exemplary method 750 of operating the reservoir volume detection device 402 via the cleaning wheel 720. In some embodiments, at least some operations in method 750 are performed by the material preparation system 102, the preparation evaluation system 104, and / or the material evaluation system 106 of instrument 100. In other embodiments, other components, units, and devices of instrument 100 are used to perform at least one operation in method 750. In some embodiments, method 750 includes operations 752, 754, 756, 758, and 760.

[0606] At operation 752, the material preparation system 102 is used to aspirate excess fluid material from the reaction reservoir 738 on the cleaning wheel 720. In some embodiments, after one or more predetermined analytical procedures on the cleaning wheel 720, excess fluid material remains in the reaction reservoir 738. It is necessary to remove this volume of excess material from the reaction reservoir 738 for subsequent processes, such as before dispensing the substrate into the reaction reservoir. Figure 4 As shown.

[0607] At operation 754, the material preparation system 102 transports the reaction reservoir 738 to the reservoir image capture unit 132 on the cleaning wheel 720.

[0608] At operation 746, the reservoir volume detection device 402 performs a remaining volume detection in the reaction reservoir 738. In some embodiments, the reaction reservoir remaining volume detection device 702 is used to perform the remaining volume detection.

[0609] At operation 748, the material preparation system 102 is used to prepare fluid materials (e.g., such as...) Figure 4 The substrate shown is dispensed into the reaction reservoir 738.

[0610] At operation 760, the reservoir volume detection device 402 performs a dispensing volume detection in the reaction reservoir 738. In some embodiments, the reaction reservoir dispensing volume detection device 700 is used to perform the dispensing volume detection.

[0611] Figure 27This is a flowchart illustrating an exemplary method 800 for operating a reaction reservoir dispensing volume detection device 700. Although method 800 is described primarily with respect to the reaction reservoir dispensing volume detection device 700, method 600 is similarly applicable to other types of reservoir volume detection devices 402. In some embodiments, method 800 is performed by a container holder device 720 (e.g., a cleaning wheel) and the reaction reservoir dispensing volume detection device 700.

[0612] Typically, if the calculated volume is outside the tolerance range, method 800 performs an analysis of the volume of fluid material dispensed or aspirated into the reservoir and labels the dispensing or aspiration results, or test results.

[0613] At operation 802, the fluid substance is dispensed into a reaction reservoir 728 supported, for example, in a container holder assembly 720, as designed. Examples of fluid substances include samples, diluents, reagents, substrates, or any combination thereof as described herein. For example, diluents or reagents are used during diagnostic mode for cleaning the wheel.

[0614] At operation 804, the container carrier assembly 720 transports the reaction reservoir 738 containing the dispensed substance to the reservoir image capture unit 132. In some embodiments, the reservoir image capture unit 132 is arranged to capture an image of the reaction reservoir 738 after dispensing without transport. In other embodiments, the dispensing at operation 802 occurs where the reservoir image capture unit 132 is positioned, and an image of the reaction reservoir 738 is captured after dispensing without moving the reaction reservoir 738.

[0615] At operation 806, the reservoir image capture unit 132 of the reaction reservoir dispensing volume detection device 700 captures an image of the reaction reservoir 738. In some embodiments, the image of the reaction reservoir 738 is a digital image of a predetermined resolution.

[0616] At operation 808, the reaction reservoir dispensing volume detection device 700 analyzes the image to determine the volume of fluid material within the reaction reservoir 738. (Refer to...) Figure 28 and 29 An example of operation 808 is described in more detail.

[0617] At operation 810, the reaction reservoir dispensing volume detection device 700 determines whether the determined volume falls within a tolerance range. When the determined volume is outside the tolerance range, the dispensing of fluid material into the reaction reservoir 738 is considered inappropriate. In some embodiments, such a tolerance range is determined based on an allowable deviation from the target dispensing volume of fluid material expected to be dispensed into the reaction reservoir 738. This tolerance range may vary depending on the target aspiration volume and other factors. By way of example, with a target dispensing volume (V) of 200 μL, it is considered acceptable if 194 μL ≤ V ≤ 206 μL. In other examples, it is considered acceptable if the standard deviation (V(n)) is equal to or less than ±1 μL.

[0618] When it is determined that the detected volume falls within the tolerance range ("Yes" is selected at operation 810), method 800 proceeds to the next predetermined step. Otherwise ("No" is selected at operation 810), method 800 proceeds to operation 812.

[0619] At operation 812, the reaction reservoir dispensing volume detection device 700 marks the dispensing to indicate that the dispensed sample volume in reaction reservoir 738 is unsuitable for subsequent processes. In other embodiments, the entire test result that has been used with the dispensed fluid substance may be marked to indicate or suggest that the test result may be incorrect. Alternatively, the reaction reservoir dispensing volume detection device 700 is used to stop the associated test or analysis process in instrument 100. In other embodiments, the evaluation results can be used to automatically adjust test results that may be erroneous due to inappropriate volumes of fluid substance (for example, within a certain volume range, the RLU is proportional to the substrate volume, and at a certain point, it exceeds the luminometer aperture range, then plateaus and decreases due to the dilution factor). In other embodiments, the evaluation results can be used to automatically adjust the volume of fluid substance in response to a volume determination.

[0620] See Figure 28 and 29 , described Figure 27 An example of operation 808, in which captured images are analyzed to determine the volume dispensed in the reaction reservoir. Specifically, Figure 28 It shows the method for execution Figure 27 A flowchart of an exemplary method 830 for operation 608. Also refer to... Figure 29 Method 830 is described, and the figure illustrates an exemplary analysis of a captured image 780 of a reaction reservoir.

[0621] At operation 832, the reaction reservoir dispensing volume detection device 700 detects a reference portion 784 of the reaction reservoir 738 in the captured image 780. In some embodiments, the reference portion 784 includes the bottom portion of the reaction reservoir 738. Other portions of the reaction reservoir 738 may be used as the reference portion 784.

[0622] Various image processing methods can be used to detect the bottom portion 784 in image 780. In some implementations, the bottom portion 784 is detected by a pattern matching function that searches for patterns representing the bottom portion based on pre-trained reference images. For example, such a pattern matching function performs a pattern search that scans the captured image to look for patterns already stored in the system and identified as bottom portions. The correlation value or matching rate (e.g., % match) is adjustable. Other methods are also possible in other implementations. An example of such image processing methods can be implemented using Cognex In-SightVision software, available from Cognex Corporation (Nartick, MA), which offers various tools such as edge detection (“Edge”), pattern matching (“Pattern Match”), and histogram analysis (“Histogram”).

[0623] At operation 834, the reaction reservoir dispensing volume detection device 700 detects the center point 786 of the bottom portion 784. For example... Figure 29 As shown, once the bottom portion 784 is detected, the center point 786 can be calculated as the midpoint of the bottom portion 784.

[0624] At operation 836, the reaction reservoir distribution volume detection device 700 detects the surface layer 788 of the distribution volume in the reaction reservoir 738. Figure 29 Various image processing methods can be used to detect the surface layer 788 in image 780. In some implementations, similar to operation 832, the surface layer 788 is detected by a pattern matching function based on a pre-trained reference image. In other implementations, other methods are also possible.

[0625] At operation 838, the reaction reservoir distribution volume detection device 700 detects the center point 790 of the surface layer 788. For example... Figure 29 As shown, once surface 788 is detected, center point 790 can be calculated as the midpoint of the straight line of surface 788.

[0626] At operation 840, the reaction reservoir dispensing volume detection device 700 measures the distance L2 between the center point 786 of the bottom portion 784 and the center point 790 of the surface portion 788. Figure 29In some implementations, distance L2 is measured as the pixel distance between center points 786 and 790 in image 780. In some implementations, the pixel distance is calculated based on the Euclidean distance between the two pixels.

[0627] At operation 842, the reaction reservoir dispensing volume detection device 700 converts distance L2 into volume based on reservoir volume correlation data 712. Figure 22 The correlation data 712 includes information about the correlation between the volume within the reaction reservoir 738 and the distance L2 between the center point 786 of the bottom portion 784 and the center points 790 of multiple different surface layers 788 within the reaction reservoir 738. In some embodiments, the correlation data 712 may be plotted on a correlation curve 860, such as... Figure 30 As shown. (Refer to...) Figure 31 An exemplary method for generating correlation data 712 is described.

[0628] Figure 30 This is an exemplary correlation curve 860 corresponding to the correlation data 712. In some embodiments, the correlation curve 860 shows the relationship between the distance L2 (e.g., pixel distance) between center points 786 and 790 and the volume V2 of the dispensed fluid substance 782 in the reaction reservoir 738. In the illustrated example, the correlation curve 860 represents the relationship between the mass of the fluid substance dispensed in the reaction reservoir 738 and the pixel height of the fluid substance in the reaction reservoir 738. This mass can be converted to volume based on the density of the fluid substance. The pixel height of the fluid substance in the reaction reservoir corresponds to the distance D2.

[0629] The correlation curve 860 can be obtained by plotting multiple discrete data points included in the correlation data 712, which will serve as a reference. Figure 31 Describe it. For example... Figure 30 As shown, the correlation curve indicates that the partition volume V2 (or mass M2) generally increases with increasing distance L2. Since the bottom portion 784 of the reaction reservoir 738 is chosen as the reference point, distance L2 is generally linearly correlated with volume V2 (or mass M2). For example, distance L2 and volume V2 are generally linearly correlated for volumes exceeding 10 μL.

[0630] Figure 31 This is a flowchart illustrating an exemplary method 870 for operating a reservoir volume correlation data generation system 710 to generate reservoir volume correlation data 712.

[0631] In some implementations, correlation data 712 is created using weight analysis. For example, the reservoir volume correlation data generation system 710 uses different volumes of fluid to display the correlation between extracted pixel distance information and fluid volume information in the reservoir. In some implementations, the reservoir volume correlation data generation system 710 selects multiple points within a target volume range (e.g., 190, 195, 200, 205, and 210 μL), assigns these volume settings to the reservoir, and takes images of the reservoir to perform pixel distance calculations. The reservoir volume correlation data generation system 710 then plots a calibration curve between the pixel distance calculated from the image and the mass measured by weight analysis. This mass is then converted to volume using the fluid density.

[0632] At operation 872, the reservoir volume correlation data generation system 710 measures the mass of an empty reservoir (such as reaction reservoir 738).

[0633] At operation 874, the reservoir volume correlation data generation system 710 distributes fluid into the reservoir.

[0634] At operation 876, the reservoir volume correlation data generation system 710 captures an image of the reservoir containing the fluid.

[0635] At operation 878, the reservoir volume correlation data generation system 710 extracts the distance between a reference portion of the reservoir (such as the bottom portion 784 of the reaction reservoir 738) and the water surface line of the fluid in the image captured in operation 876. In some embodiments, the distance is measured by pixel distance. In some embodiments, this distance is determined similarly to at least some operations of method 830 (such as operations 832, 834, 836, 838, and 840). In other embodiments, other methods are also possible.

[0636] During operations 880, 882, and 884, the reservoir volume correlation data generation system 710 measures the volume of fluid dispensed into the reservoir. Various methods can be used to determine the fluid volume. In the illustrated example, the gravimetric method is used as described below.

[0637] At operation 880, the reservoir volume correlation data generation system 710 measures the mass of the reservoir containing the dispensed fluid.

[0638] At operation 882, the reservoir volume correlation data generation system 710 calculates the mass of the fluid contained in the reservoir. In some embodiments, the mass of the fluid in the reservoir (obtained at operation 880) can be calculated by subtracting the mass of the empty reservoir (obtained at operation 872) from the total mass of the reservoir containing the fluid.

[0639] At operation 884, the reservoir volume correlation data generation system 710 converts fluid mass into volume based on fluid density.

[0640] At operation 886, the reservoir volume correlation data generation system 710 correlates the distance calculated at operation 878 with the volume obtained at operation 884.

[0641] At operation 888, the reservoir volume correlation data generation system 710 determines whether a sufficient number of correlations have been performed to generate reservoir volume correlation data 712. If so (yes is selected at operation 888), method 870 proceeds to operation 890. Otherwise (no is selected at operation 888), method 870 returns to operation 874, where another fluid is allocated to the reservoir, and subsequent operations are performed to determine additional correlations between distance and the volume of fluid within the reservoir. To obtain a sufficient range of correlation data, different amounts of fluid are allocated to the reservoir in different correlation cycles. Furthermore, for some correlation cycles, the amount of fluid allocated to the reservoir can generally be kept the same to obtain reliable correlation results.

[0642] At operation 890, the reservoir volume correlation data generation system 710 creates reservoir volume correlation data 712 based on multiple correlations performed at operation 886. In some embodiments, the correlation data 712 is displayed as a correlation curve by plotting the pixel distance of each image against the corresponding allocated volume (e.g., Figure 30 The correlation curve (860) is used to estimate the relationship between distance and volume in a reservoir.

[0643] See Figures 32 to 34 An exemplary operation of the reaction reservoir remaining volume detection device 702 is described.

[0644] Figure 32 This is a flowchart illustrating an exemplary method 900 for operating the reaction reservoir remaining volume detection device 702. In some embodiments, method 900 includes operations 902, 904, 906, 908, 910, and 912.

[0645] Generally, Method 900 performs an analysis of the reservoir to determine whether it contains residual volume after aspiration. If the reservoir contains volume exceeding tolerance, the aspiration result or test result is marked.

[0646] At operation 902, the reaction reservoir remaining volume detection device 702 draws material from the reservoir (such as reaction reservoir 738).

[0647] At operation 904, the reservoir remaining volume detection device 702 transports the reservoir to the reservoir image capture unit 132. In some embodiments, the reservoir image capture unit 132 is arranged to capture an image of the reservoir after aspiration without transport. In other embodiments, aspiration at operation 902 occurs where the reservoir image capture unit 132 is positioned, and an image of the reservoir is captured without moving the reservoir after aspiration.

[0648] At operation 906, the memory image capture unit 132 captures an image of the memory. In some embodiments, the image of the memory is a digital image with a predetermined resolution.

[0649] At operation 908, the reaction reservoir remaining volume detection device 702 analyzes the image to determine the presence of substances within the reservoir. (Refer to...) Figure 33 and 34 An example of operation 908 is described in more detail.

[0650] At operation 910, the reaction reservoir remaining volume detection device 702 determines whether the presence of remaining volume falls within a tolerance range. When the presence of remaining volume exceeds the tolerance range, aspiration of material from the reservoir is considered inappropriate. The tolerance range represents the range of remaining volume in the reaction reservoir that is tolerable for acceptable test results. For example, for acceptable test results, it is not necessary to aspirate the reaction reservoir completely. In some embodiments, such a tolerance range is determined based on the pattern matching score between the captured image and the pre-trained image, such as... Figure 33 As further described in the text. By way of example, when a remaining volume of 4 μL or less in the reaction reservoir is considered acceptable, a pattern matching score that can be interpreted as an image similar to a reaction reservoir containing a 4 μL volume can be used as a tolerance threshold.

[0651] When it is determined that the presence of the remaining volume falls within the tolerance range ("Yes" is selected at operation 910), method 900 proceeds to the next predetermined step. Otherwise ("No" is selected at operation 910), method 900 proceeds to operation 812.

[0652] At operation 912, the reaction reservoir remaining volume detection device 702 marks the aspiration result to indicate that aspiration from the reservoir is unsuitable for subsequent processes. In other embodiments, the entire test result that has been used to aspirate the reservoir may be marked to indicate or suggest that the test result may be incorrect. Alternatively, the reaction reservoir remaining volume detection device 702 is used to stop the associated test or analysis process in instrument 100. In other embodiments, the evaluation result can be used to automatically adjust for test results that may be erroneous due to inappropriate volumes of fluid substances.

[0653] See Figure 33 and34 , described Figure 32 An example of operation 908, in which the captured image is analyzed to determine the remaining volume 952 within the reservoir. Specifically, Figure 33 It shows the method for execution Figure 32 The flowchart illustrates an exemplary method 930 of operation 908. See also the flowchart... Figure 34 Method 930 is described, and the figure illustrates an exemplary analysis of a captured image 942 of the reservoir.

[0654] At operation 932, the reaction reservoir remaining volume detection device 702 detects a region of interest 946 in the captured image 942. In some embodiments, the region of interest 946 includes the bottom portion of the reservoir 944. In some embodiments, the reservoir 944 in the image represents the aforementioned reaction reservoir 738. Other portions of the reaction reservoir 738 may be used as reference portions 784.

[0655] Various image processing methods can be used to detect the bottom portion 946 in image 942. In some implementations, the bottom portion 946 is detected by a pattern matching function that searches for patterns representing the bottom portion based on pre-trained reference images. For example, such a pattern matching function performs a pattern search that scans the captured image to look for patterns already stored in the system and identified as the bottom portion. The correlation value or matching rate (e.g., % match) is adjustable. Other methods are also possible in other implementations. An example of such image processing methods can be implemented using Cognex In-SightVision software, available from Cognex Corporation (Nartick, MA), which offers various tools such as edge detection (“Edge”), pattern matching (“Pattern Match”), and histogram analysis (“Histogram”).

[0656] At operation 934, the reaction reservoir remaining volume detection device 702 compares the region of interest 946 with a reference image 948. In some embodiments, the reference image 948 includes a portion 950 corresponding to the region of interest 946. In other embodiments, the reference image 948 is only the portion 950 corresponding to the region of interest 946 of the captured image 942.

[0657] In some embodiments, reference image 948 represents an image of the same reservoir 944 when it is empty. Since ideal suction leaves no residual fluid at the bottom of reservoir 944, a pre-trained image of an empty reservoir 944 is used as reference image 948. In other embodiments, other images may be used as reference image 948.

[0658] At operation 936, the reaction reservoir residual volume detection device 702 generates a match score between captured image 942 and reference image 948. This match score indicates how well captured image 942 matches reference image 948. This match score is used as a measure to determine the threshold value for the presence of excess residual fluid in the reservoir.

[0659] At operation 938, the reaction reservoir residual volume detection device 702 determines whether the matching score meets a threshold. If the matching score meets the threshold (yes is selected at operation 938), it is assumed that there is no residual fluid or a tolerable amount of residual fluid in the reservoir, and method 930 proceeds to the predetermined next step. Otherwise (no is selected at operation 938), method 930 continues at operation 940. For example, if the matching score is below a predetermined threshold or cutoff value, it is assumed that there is excess residual fluid in the reservoir, and method 930 proceeds to operation 940.

[0660] At operation 940, the reaction reservoir remaining volume detection device 702 marks the aspiration result to indicate that aspiration from the reservoir is unsuitable for subsequent processes. In other embodiments, the entire test result that has been used to aspirate the reservoir may be marked to indicate or suggest that the test result may be incorrect. Alternatively, the reaction reservoir remaining volume detection device 702 is used to stop the associated test or analysis process in instrument 100. In other embodiments, the evaluation result can be used to automatically adjust for test results that may be erroneous due to inappropriate volumes of fluid substances.

[0661] Alternatively, Method 930 uses other methods for image comparison and boundary assignment. Examples of such methods utilize general classification tools such as logistic regression, support vector machines, neural networks, convolutional neural networks, and classification trees.

[0662] See Figure 35 and 36 An exemplary operation of the allocation adjustment device 704 is described.

[0663] Figure 35 A block diagram of an exemplary system 960 in which the allocation adjustment device 704 operates.

[0664] Typically, the dispensing adjustment device 704 can use the volume measurement capacity of the reservoir image capture unit 132 to perform onboard adjustments of the pipette and pump, thereby improving pipetting accuracy and overall system precision. In the illustrated example, a single or multiple volume dispensing is performed in the reservoir, which is then transferred to a cleaning wheel for measurement. The results of the volume measurements performed by the reaction reservoir dispensing volume detection device 700 as described above can be obtained, and the dispensing adjustment device 704 determines the accuracy of each combination of pump and pipette. In some embodiments, the measurement volume associated with the pump is used to adjust the operating parameters of the pump and pipette combination. By way of example, the step resolution of each pump can be adjusted, or an offset can be added to the software instructions of each pump. After adjustment, the dispensing adjustment device 704 can recheck the pump accuracy and readjust the pump as needed. In some embodiments, the dispensing adjustment device 704 performs this adjustment operation while the instrument is idle to facilitate clinical testing. In other embodiments, the dispensing adjustment device 704 performs the adjustment operation during instrument initialization. In some implementations, the distribution adjustment device 704 periodically performs adjustment operations to monitor trends in pump performance, allowing users or service departments to remotely monitor the status and make maintenance decisions, such as when to dispatch service engineers for maintenance or parts replacement.

[0665] like Figure 35 As shown, the material preparation system 102 dispenses fluid material 118 into one or more reservoirs 114 (e.g., reaction reservoir 728 on a washing wheel). Then, as described herein, a reaction reservoir dispensing volume detection device 700 performs a volume measurement in the reservoir 114 and provides the volume measurement result 962 to a dispensing adjustment device 704. In some embodiments, the dispensing adjustment device 704 analyzes the volume measurement result 962 and generates calibration information 964, which can then be used to calibrate the material preparation system 102 to improve dispensing accuracy.

[0666] Figure 36 This is a flowchart illustrating an exemplary method 970 for operating the distribution adjustment device 704. In some embodiments, method 970 includes operations 972, 974, 976, 978, 980, and 982.

[0667] At operation 972, the dispensing adjustment device 704 receives one or more operating parameters from the material preparation system 102. As described above, the material preparation system 102 includes one or more material dispensing devices, such as sample transfer device 152, reagent transfer device, and substrate transfer device 178, for dispensing fluid material 118 into reservoir 114. The operating parameters include various information regarding the configuration, settings, and operating status of the material dispensing devices. In some embodiments, these material dispensing devices include a pump device that operates the dispensing unit (e.g., a pipette). Some examples of pump devices are operated by various types of motors, such as stepper motors. When using a stepper motor, the operating parameters may include the step resolution, which is controlled to adjust the dispensing amount via the pipette.

[0668] At operation 974, the dispensing adjustment device 704 receives the target dispensing volume of fluid substance 118. The target dispensing volume represents the volume of fluid substance 118 expected to be dispensed into reservoir 114 based on the operating parameters of the dispensing device.

[0669] At operation 976, the allocation adjustment device 704 receives the detected volume that has been allocated to the storage 114.

[0670] At operation 978, the dispensing adjustment device 704 compares the detected volume with the target volume. By way of example, a first material dispensing device, including a first pump device using a first suction pipette, is configured to dispense a target volume of 100 μL into a reservoir. After dispensing, a volume of 99.9 μL is detected dispensed into the reservoir. The dispensing adjustment device 704 then compares the 100 μL target volume with the detected volume of 99.9 μL and determines that there is a difference of 0.1 μL between the target volume and the detected volume in the first material dispensing device.

[0671] In some embodiments, multiple dispensing instances from a single dispensing device are considered a group. For example, a particular dispensing device uses a pump and reservoirs (or three reservoirs) to perform a first, second, and third dispensing, with a target volume of 100 μL. After the three dispensing instances, the volume dispensed into the reservoir in the first dispensing instance is detected to be 100.5 μL, in the second dispensing instance 99.5 μL, and in the third dispensing instance 100 μL. In some embodiments, all detected volumes can be used together to calibrate the dispensing device. For example, the standard deviation of the three detected volumes (e.g., 0.5 μL in this example) can be used to calibrate the dispensing device by, for example, adjusting the step resolution of the stepper motor of the dispensing device. In this example, calibration information 964 is generated and used to reduce the standard deviation. In other embodiments, as described above, each detected volume can be used to calibrate the dispensing device for each dispensing instance.

[0672] In other embodiments, multiple dispensing events from multiple dispensing devices are considered a group. For example, a first dispensing device performs a first dispensing, a second dispensing device performs a second dispensing, and a third dispensing device performs a third dispensing, with a target volume of 100 μL. After dispensing, the volume dispensed by the first dispensing device is detected as 100.5 μL, the volume dispensed by the second dispensing device is detected as 99.5 μL, and the volume dispensed by the third dispensing device is detected as 100 μL. In some embodiments, all detected volumes can be used together to calibrate the dispensing devices. For example, the standard deviation of the three detected volumes (e.g., 0.5 μL in this example) can be used to calibrate the dispensing devices by, for example, adjusting the stepping resolution of the stepper motors of the dispensing devices. In this example, calibration information 964 is generated and used to reduce the standard deviation. In other embodiments, as described above, the detected volumes can be used to calibrate the respective dispensing devices.

[0673] At operation 980, the dispensing adjustment device 704 generates calibration information 964 for the material dispensing device. The calibration information 964 includes information for controlling the material dispensing device so that the volume dispensed by the device is closer to the target volume. If the material dispensing device includes a stepper motor, the calibration information 964 includes adjustments to the stepping resolution of the stepper motor, thereby adjusting the volume dispensed by the stepper motor.

[0674] At operation 982, the dispensing adjustment device 704 adjusts the operating parameters of the material dispensing device based on calibration information 964. The material dispensing device can be used to dispense the same or different volumes based on the modified operating parameters. In the example above, the three dispensing instances are considered a group, and the volume allocated to the container after calibration is checked again.

[0675] See Figures 37 to 39 An exemplary operation of the reaction reservoir detection device 706 is described.

[0676] Figure 37 This is a flowchart illustrating an exemplary method 1000 for operating a reaction reservoir detection device 706. In some embodiments, method 1000 includes operations 1002, 1004, 1006, 1008, 1010, and 1012.

[0677] Typically, during system initialization or reset, it is necessary to remove the reservoirs within the cleaning wheel. The reservoir detection device 706 can utilize the reservoir image capture unit 132 to determine whether all or some of the reservoirs have been removed during this initialization sequence. In some embodiments, the cleaning wheel is used to rotate to each position such that each reservoir position is checked by the image capture unit. At each cleaning wheel rotation position, the reservoir detection device 706 can perform image processing, such as a pattern matching algorithm, to check the presence of the reservoir by comparing the captured image with a reference image (e.g., an image of the cleaning wheel without containers). Unlike other methods of observing or utilizing the volume within the reservoir, the reservoir detection device 706 according to the exemplary embodiments of this disclosure provides reliable results. As the reservoir detection device 706 searches for a close match to the reservoir geometry, a large deviation from the reference image will indicate the presence of the reservoir, and a small deviation will indicate its absence. If presence is determined, the system can remove the reservoir and check again to confirm that the reservoir has been successfully removed. Once it is determined that no reservoir is present at a given cleaning wheel position, the cleaning wheel can rotate to the next position and the process can be repeated.

[0678] In the example shown, the reaction reservoir detection device 706 is described primarily with respect to the cleaning wheel 720. However, in other embodiments, the reaction reservoir detection device 706 is used in conjunction with other types of container rack devices.

[0679] At operation 1002, the reaction reservoir detection device 706 uses the reservoir image capture unit 132 to capture the reservoir tank 1044 on the cleaning wheel 720. Figure 39 (e.g., slot 736) image.

[0680] At operation 1004, the reaction reservoir detection device 706 analyzes the image to determine the reservoir 1042 on the cleaning wheel 720. Figure 39 (For example, the presence or absence of reaction reservoir 738). See reference. Figure 38 and 39 An example of operation 1004 is described in more detail.

[0681] At operation 1006, the reaction reservoir detection device 706 determines whether a reservoir exists in the reservoir tank. Otherwise (select "No" at operation 1006), method 1000 continues at operation 1008. Otherwise (select "No" at operation 1006), method 1000 proceeds to operation 1010.

[0682] At operation 1008, the reaction reservoir detection device 706 removes the reservoir from the reservoir tank of the cleaning wheel 720. In other embodiments, other devices in instrument 100 (such as...) Figure 2The transfer or bracket device shown is used to remove the reservoir from the cleaning wheel 720. In other embodiments, the reservoir is removed manually from the cleaning wheel 720.

[0683] At operation 1010, the reaction reservoir detection device 706 determines whether all positions of the cleaning wheel 720 have been analyzed through previous operations (e.g., operations 1002, 1004, 1006, and 1008). If so (selecting "Yes" at operation 1010), method 1000 proceeds to the predetermined next step. Otherwise (selecting "No" at operation 1010), method 1000 proceeds to operation 1012.

[0684] At operation 1012, the reaction reservoir detection device 706 moves the cleaning wheel 720 to the next position and repeats operation 1002 and subsequent operations.

[0685] See Figure 38 and 39 , described Figure 37 Example of operation 1004, in which captured images are analyzed to determine the presence of a reservoir on the cleaning wheel. Specifically, Figure 38 It shows the method for execution Figure 37 A flowchart of an exemplary method 1020 for operation 1004. Also refer to... Figure 39 Method 1020 is described, and the figure illustrates an exemplary analysis of a captured image 1040 of a reservoir 1044 on a cleaning wheel.

[0686] At operation 1022, the reservoir detection device 706 detects a region of interest 1046 in the captured image 1040. In some embodiments, the region of interest 1046 includes at least a portion of the reservoir trough 1044 (e.g., trough 736) of the washing wheel 720. In some embodiments, the region of interest 1046 includes the bottom portion of the reservoir, or a portion of the image corresponding to the bottom portion of the reservoir. An exemplary method for detecting the region of interest can be implemented using Cognex In-Sight Vision software, available from Cognex Corporation (Nartick, MA), which provides various tools such as edge detection (“Edge”), pattern matching (“Pattern Match”), and histogram analysis (“Histogram”).

[0687] At operation 1024, the reactor detection device 706 compares the region of interest 1046 with the reference image 1048. In some embodiments, the reference image 1048 includes a portion corresponding to the region of interest 1046. In other embodiments, the reference image 1048 itself corresponds to the region of interest 1046 of the captured image 1040.

[0688] In some embodiments, reference image 1048 shows an image of a reservoir 1044 in which there is no reservoir 1042. Figure 39 In other embodiments, other images may be used as reference image 948. For example, a reference image is an image of a reservoir tank having a reservoir.

[0689] At operation 1026, the reservoir detection device 706 generates a matching score between the captured image 1040 and the reference image 1048. This matching score indicates how well the captured image 1040 matches the reference image 1048. The matching score is used as a measure to determine the boundary value of the presence of reservoir 1042 in the tank 1044 of the cleaning wheel 720.

[0690] At operation 1028, the reaction reservoir detection device 706 determines whether the matching score meets a threshold. If the matching score meets the threshold (yes is selected at operation 1028), it is assumed that no reservoir exists in the groove of the cleaning wheel, and method 1020 proceeds to operation 1030. Otherwise (no is selected at operation 1028), it is assumed that a reservoir exists in the groove of the cleaning wheel, and method 1020 continues at operation 1032. For example, if the matching score is below a predetermined threshold or boundary value, it is assumed that a reservoir exists in the groove of the cleaning wheel, and method 1020 proceeds to operation 1032.

[0691] At operation 1030, the reaction reservoir detection device 706 confirms that there is no reservoir 1042 in the tank 1044 of the cleaning wheel 720.

[0692] At operation 1032, the reaction reservoir detection device 706 confirms the presence of reservoir 1042 in the tank 1044 of the cleaning wheel 720.

[0693] For reference Figures 22 to 39As shown, the container volume detection device 402 can be modified to suit various applications. For example, the container volume detection device 402 can be applied to any analyzer used for preparing and / or detecting analytes of interest using fluid substances, such as in vitro diagnostic (IVD) analyzers. In some embodiments, the container volume detection device 402 and its method can be applied to any device or unit other than a cleaning wheel. Some embodiments of the container volume detection device 402 can be applied to total reaction volume checks. In some embodiments, the calibration curve used in the container volume detection device 402 is established between pixel distance and colorimetric volume results obtained using a spectrophotometer. In other embodiments, the calibration curve used in the container volume detection device 402 is established between pixel distance and alkaline phosphatase reaction results obtained using a photon counting module. In other embodiments, the calibration curve used in the container volume detection device 402 is established using a JIG reaction reservoir, where a line with a known volume height is on the outer wall. For the detection of remaining volume in the container volume detection device 402 (e.g., for volumes greater than 10 μL), line finding or grayscale matching can be applied.

[0694] The container volume detection device 402 according to the exemplary embodiments of this disclosure can be used in a variety of other applications. In some embodiments, the container volume detection device 402 is used to detect misalignment of the dispensing tip. For example, the container image capture unit 132 is used to determine whether the dispensing tip is off-center when it enters the field of view. In other embodiments, the container volume detection device 402 is used to detect wheel positioning integrity. For example, the container image capture unit 132 is used to determine whether the washing wheel is tilted or misaligned. In other embodiments, the container volume detection device 402 is used to detect any anomalies, such as splashing, bubbling, or poor magnetization. In other embodiments, the container volume detection device 402 is used to detect RV integrity, such as scratches, discoloration, and translucency. In other embodiments, the container volume detection device 402 is used to detect tip alignment integrity.

[0695] The light source used in the reservoir volume detection device 402 does not need to be located behind the reaction reservoir. Other locations for the backlight device are also possible. Alternatively, the light source may be integrated into a camera unit and configured to illuminate from the camera unit. Such a light source integrated into the camera unit can be used with a screen located behind the reaction reservoir, as shown herein. In some embodiments, the camera unit used in the reservoir volume detection device 402 is configured to use IR spectroscopy to monitor the temperature of the reservoir and / or the cleaning wheel.

[0696] As described above, the reservoir volume detection device 706 and the reaction reservoir detection device 402 can be applied to any container rack device other than the cleaning wheel. As described above, the dispensing adjustment device 704 of the reservoir volume detection device 402 can be used to measure the level of the substrate volume and use the measured level to adjust the test results of the RLU, fine-tune the calibration, and improve accuracy.

[0697] Instrument 100 according to exemplary embodiments of this disclosure employs various procedural solutions to perform image evaluation operations, such as pattern matching, as described herein. In some embodiments, such procedural solutions are developed using off-the-shelf software solutions. An example of a procedural solution is the In-Sight Explorer, purchased from Cognex Corporation (Nartick, MA). (Also known as In-Sight Vision Software).

[0698] See now Figure 40 The accompanying figures illustrate an example of the tip evaluation system 122.

[0699] Figure 40 yes Figure 1 A block diagram of an example of a distribution tip evaluation system 122. In some embodiments, the distribution tip evaluation system 122 includes a distribution tip integrity evaluation device 1100.

[0700] The dispensing tip integrity assessment device 1100 is used to evaluate the quality of the fluid material 118 aspirated into the dispensing tip 112 and the alignment of the dispensing tip 112. As described herein, the dispensing tip 112 can be of various types and used in different processes. An example of the dispensing tip 112 is a suction tip that can be used with the sample transfer device 152. The dispensing tip integrity assessment device 1100 may utilize the dispensing tip image capture unit 130. Reference Figure 41 An example of the allocation tip integrity assessment device 1100 is illustrated and described in more detail.

[0701] Figure 41 yes Figure 40 A block diagram of an example of a tip integrity assessment device 1100. In some embodiments, the tip integrity assessment device 1100 includes a sample quality detection device 1112 and a tip alignment detection device 1114.

[0702] In some implementations, the tip integrity assessment device 1100 utilizes Figure 10 The sample aspiration system 510 is implemented. In other embodiments, the dispensing tip integrity assessment device 1100 can be used in other types of systems that can utilize containers for aspiration or dispensing of fluid substances.

[0703] The sample quality detection device 1112 is used to detect the quality of the sample drawn into the sample transfer tip of the sample transfer device 152. (Reference) Figures 42 to 55 An example of the structure and operation of the sample quality testing device 1112 is described.

[0704] In addition to detecting sample quality at the dispensing tip, the sample quality detection device 1112 can also be used to detect the quality of the fluid substance 118 contained in the reservoir 114. As described herein, the reservoir 114 can be of various types and used in different processes. Examples of reservoirs 114 include reaction reservoirs, sample reservoirs, and diluent reservoirs, which are used throughout the instrument 100. In some embodiments, the sample quality detection device 1112 may use the reservoir image capture unit 132.

[0705] Tip alignment detection device 1114 is used to detect tolerances and misalignments of the dispensing tip 112 relative to the sample aspiration module 512 and / or the dispensing tip image capture unit 130. For example, allowable tolerances and / or misalignments of the dispensing tip 112 can reduce the accuracy of detecting the volume of sample aspirated into the dispensing tip 112, as performed by the dispensing tip volume detection device 400 herein. Tip alignment detection device 1114 is also used to adjust or correct the detected volume of liquid aspirated into the dispensing tip 112 based on the detection of tolerances and misalignments. Reference Figures 56 to 68 An example of the structure and operation of the tip alignment detection device 1114 is described.

[0706] See Figures 42 to 55 An example of a sample quality testing device 1112 is described.

[0707] Figure 42 An example of a sample quality inspection device 1112 is shown. In some embodiments, the sample quality inspection device 1112 includes an image capture device 1120, an image evaluation device 1122, a classification data generation device 1124, and a classification device 1126. Also shown are aspirated sample 1130, image 1132, one or more color parameters 1134, classification data 1136, and sample classification result 1138.

[0708] The sample quality detection device 1112 is used to evaluate the quality of the sample aspirated through the dispensing tip and determine whether the sample has sufficient quality for subsequent analysis. If the sample quality is determined to be compromised, the instrument can notify the user of the sample quality and / or stop the test.

[0709] In some implementations, the sample provided in the sample tube (e.g., Figure 4Sample 324 contains various interfering substances or contaminants that may compromise sample integrity and affect laboratory testing. Samples containing interfering substances in amounts greater than tolerable levels may produce erroneous but reliable results that are not easily detected. Examples of interfering substances for chemical and immunoassay systems include hemoglobin, bilirubin (also referred to herein as jaundice, a medical condition caused by bilirubin), and lipids (also referred to herein as hyperlipidemia, a medical condition caused by lipids). The concentrations of hemoglobin, jaundice, and hyperlipidemia should be limited to predetermined levels according to the assay to ensure that no interference occurs and to avoid skewed results.

[0710] Various methods have been used to assess sample quality. Some examples of these methods include chemical analyzers using spectrophotometers. Determining sample quality using such a spectrophotometer is a separate event resulting from the chemical analysis of the sample, and therefore may require additional samples to determine sample integrity, depending on the manufacturer. Because spectrophotometers use specific wavelengths for measurement, the system requires LEDs or collimated light sources, and complex mathematical processing is used due to spectral overlap between interfering substances and some of the final products being measured. Additionally, hyperlipidemic samples often exhibit volume shifts, which affect the sample volume during testing. Therefore, methods for assessing sample quality thus require separate testing and incur additional costs. Consequently, primary sample testing is postponed because it can only be performed after quality checks. Alternatively, in cases where primary sample testing and sample quality testing are performed simultaneously, damaged samples can only be marked during or after the primary sample testing. In this case, the sample needs to be redrawn, which also leads to delays in test results.

[0711] Conversely, the sample integrity detection device 1112 is integrated with the instrument 100, and utilizes the various components of the instrument 100 configured for sample analysis. Therefore, a single instrument can both assess sample quality and perform sample analysis without causing delays or additional costs.

[0712] As described above, in some embodiments, the sample integrity detection device 1112 and Figure 10 The sample aspiration system 510 is used in conjunction with it. In other embodiments, the sample integrity detection device 1112 can be used in other types of systems that can utilize containers to aspirate fluid substances.

[0713] In the illustrated example, the sample integrity detection device 1112 is described primarily within the context of an immunoassay analyzer, such as... Figure 2 and 4As shown. For example, sample integrity detection device 1112 is used to detect the concentration of interfering substances such as hemoglobin, jaundice, and hyperlipidemia in a sample aspirated in the dispensing tip. However, in other embodiments, sample integrity detection device 1112 is used to assess the quality of samples in other types of instruments.

[0714] Typically, the sample integrity detection device 1112 acquires an image of a transparent conical container containing fluid. The device then extracts information about corresponding pixels within a region of interest in the image. This pixel information is used to classify the fluid. The sample integrity detection device 1112 includes a classifier model that employs a classifier to categorize fluids. If the color of the fluid drawn into the container is outside a predetermined specification range, the drawing or test is flagged. In some embodiments, when fluid integrity is determined to exceed the specifications for a given fluid, the operator of the instrument receives information about the fluid drawing.

[0715] See also Figure 42 The image capturing device 1120 is used to capture an image 1132 of the sample 1130 aspirated by the dispensing tip 1180. Figure 45 In some implementations, sample 1130 is an example of sample 540, and dispensing tip 1180 is an example of dispensing tip 112, as... Figure 10As shown in the diagram. In some embodiments, the image capture device 1120 is used to capture more than one image of the sample 1130 drawn in by the dispensing tip 1180 at different time intervals. For example, the image capture device 1120 is used to sequentially capture two images of the sample 1130 drawn in by the dispensing tip 1180 at approximately thirty (30) millisecond intervals or any other time interval. In some embodiments, the image capture device 1120 utilizes a dispensing tip image capture unit 130, which includes a camera unit 550 and a light source 552. In some embodiments, the light source 552 of the image capture device 1120 produces a white backlight. In other embodiments, the light source 552 provides one or more colored backlights, which may be fixed or variable during image capture. In some embodiments, the light source 552 may produce backlight using different exposure times. For example, the light source 552 may produce backlight using an exposure time of approximately six (6) milliseconds, and the image capture device 1120 is used to capture a first image immediately after an exposure time of approximately six (6) milliseconds and a second image after approximately thirty (30) seconds. In one embodiment, a first image is obtained approximately 0.2 seconds after the reagent is dispensed into the container. In another embodiment, a second image is obtained approximately 6.5 seconds after mixing. In yet another embodiment, a first image is obtained approximately 0.2 seconds after the reagent is dispensed into the container, and a second image is obtained approximately 6.5 seconds after mixing. Changing the exposure time can improve the evaluation of color parameters of the captured image. For example, if the sample has a high concentration, a longer exposure time may result in a brighter image, allowing the image evaluation device 1122 to effectively evaluate different color parameters.

[0716] Image evaluation device 1122 is used to process and evaluate captured image 1132 and generate one or more color parameters 1134. Color parameters 1134 are used to determine the concentration level of interfering substances contained in sample 1130. (Reference) Figures 44 to 48 An example of the image evaluation device 1122 is illustrated and described in more detail.

[0717] The classification data generation device 1124 is used to generate classification data 1136. As described below, the classification data 1136 includes a list of classification labels for different amounts of interfering substances, which are used by the classification device 1126 to generate sample classification results 1138. (Reference) Figures 49 to 53 An example of the classification data generation device 1124 is illustrated and described in more detail.

[0718] The sorting device 1126 is used to generate a sample sorting result 1138 based on the color parameter 1134 and the sorting data 1136. The sample sorting result 1138 includes information indicating the quality of the sample 1130. For example, the sample sorting result 1138 includes information indicating the concentration level of interfering substances (such as hemoglobin, jaundice, and hyperlipidemia) in the aspirated sample 1130, and (alone or in combination) indicates that the concentration level of the interfering substances is acceptable. Therefore, the sample sorting result 1138 is used to determine whether the sample 1130 has sufficient quality for laboratory analysis in instrument 100. Reference Figures 54 to 55 An example of the classification device 1126 is illustrated and described in more detail.

[0719] Figure 43 This is a flowchart illustrating an exemplary method 1150 for operating the sample integrity testing apparatus of FIG1112. In some embodiments, method 600 comprises a sample aspiration system 510 ( Figure 10 The sample integrity testing device 1112 is used for the test.

[0720] Generally, Method 1150 analyzes the sample quality in the dispensing tip based on the concentration of interfering substances (e.g., hemoglobin, jaundice (bilirubin), and hyperlipidemia), and labels the test results if the assessed quality is classified as outside the acceptable range.

[0721] At operation 1152, the sample aspiration system 510 is used to aspirate fluid material (such as sample 1130) into the dispensing tip 1180 according to its design. Figure 45 (It is like) Figure 10 In an example of the distribution tip 112 shown.

[0722] At operation 1154, the sample aspiration system 510 transports the dispensing tip 1180, containing the sample 1130 aspirated, to the image capture device 1120 (which includes a dispensing tip image capture unit 130). In some embodiments, the dispensing tip image capture unit 130 of the image capture device 1120 is arranged to capture an image of the dispensing tip 1180 after aspiration without transport.

[0723] At operation 1156, the dispensing tip image capture unit 130 captures image 1132 of dispensing tip 1180. In some embodiments, image 1132 of dispensing tip 1180 is a digital image of a predetermined resolution. In some embodiments, dispensing tip image capture unit 132 may capture more than one image of dispensing tip 1180 at varying time intervals. For example, dispensing tip image capture unit 132 may capture two images of dispensing tip 1180 at approximately thirty (30) millisecond intervals or any other time interval. At operation 1158, sample integrity detection device 1112 analyzes image 1132 to determine the content of interfering substances in sample 1130 within dispensing tip 1180. (Refer to...) Figures 44 to 55 An example of operation 1158 is described in more detail.

[0724] At operation 1160, the sample integrity detection device 1112 determines whether the content of interfering agent falls within the tolerance range. When the determined content is outside the tolerance range, aspiration of sample 1130 into dispensing tip 112 is considered inappropriate. The tolerance range can vary depending on the type of sample and / or the type of interfering agent present. In some embodiments, a classification identifier or classifier may be used to assess whether the determined content of interfering agent falls within the tolerance range, as described below.

[0725] When it is determined that the detected interfering content falls within the tolerance range (yes is selected at operation 1160), method 1150 proceeds to the next predetermined step. Otherwise (no is selected at operation 1160), method 1150 proceeds to operation 1162.

[0726] At operation 1162, the sample integrity detection device 1112 marks the aspiration to indicate that the aspirated sample 1130 in the dispensing tip 1180 is not suitable for subsequent processes. In other embodiments, the entire test result using the aspirated sample may be marked to indicate or suggest that the test result may be incorrect. Alternatively, the sample integrity detection device 1112 is used to stop the associated test or analysis process in instrument 100. In other embodiments, the evaluation results can be used to automatically adjust for test results that may be erroneous due to impaired sample quality.

[0727] refer to Figures 44 to 55 , described Figure 43 Operation 1158 involves analyzing the captured image 1132 and determining the quality of the sample aspirated into the dispensing tip. In some embodiments, operation 1158 is performed by the image evaluation device 1122, the classification data generation device 1124, and the classification device 1126 of the sample integrity detection device 1112.

[0728] Figure 44 This shows the operation. Figure 42A flowchart of an exemplary method 1170 of the image evaluation apparatus 1122. In some embodiments, method 1170 includes operations 1172, 1174, and 1176. Also refer to... Figure 45 Method 1170 is described, and the figure illustrates an exemplary analysis of captured image 1132.

[0729] At operation 1172, image evaluation device 1122 locates the assignment tip 1180 in image 1132. Various image processing methods can be used to detect the location of the assignment tip 1180 in image 1132. In some embodiments, the assignment tip 1180 is located using a pattern matching function that searches for patterns representing the assignment tip based on a pre-trained reference image. This image processing method can be implemented in various programming languages, such as Python (e.g., its contour-finding function). An exemplary method of such image processing can be implemented using Cognex In-Sight Vision software, available from Cognex Corporation (Nartick, MA), which provides various tools such as edge detection (“Edge”), pattern matching (“Pattern Match”), and histogram analysis (“Histogram”).

[0730] At operation 1174, the image evaluation device 1122 detects a predetermined region of interest 1182. The region of interest 1182 is the area of ​​image 1132 being evaluated to determine the quality of sample 1130 in dispensing tip 1180. The region of interest 1182 is preset to be a repeatable detection area because sample 1130 is included in different images 1132. Various methods can be used to detect the region of interest 1182. (See reference...) Figure 46 An example of such a method is described. In some implementations, there may be more than one predetermined region of interest, and therefore, the image evaluation device 1122 detects more than one predetermined region of interest. For example, there may be three predetermined regions of interest: a first region of interest above region of interest 1182, a second region of interest such as region of interest 1182, and a third region of interest below region of interest 1182.

[0731] At operation 1176, image evaluation device 1122 extracts color parameters 1134 from captured image 1132. Figure 42 In some implementations, the region of interest 1182 in image 1132 is analyzed to generate color parameters 1134. (See reference...) Figure 47 and 48 An example of extracting color parameters is described.

[0732] Figure 46This is a flowchart illustrating an exemplary method 1190 for finding a region of interest 1182 in image 1132. In some embodiments, method 1190 includes operations 1192 and 1194. Also referenced... Figure 45 Method 1190 is described.

[0733] Generally, once the location of the dispensing tip 1180 is determined, the image evaluation device 1122 uses a set of offset factors to determine the region of interest 1182. In some embodiments, the region of interest 1182 is optimized to include a sub-portion of the dispensing tip image, which is approximately located at the center of the vertical and horizontal axes of the sample 1130 in the dispensing tip 1180, such that the region of interest 1182 is typically located at the center of the aspirated sample 1130. In other embodiments, other locations for the region of interest 1182 are also possible. In other embodiments, as previously described, there may be more than one region of interest.

[0734] At operation 1192, the image evaluation device 1122 locates a reference line associated with the distribution tip 1180. In some embodiments, the reference line is the longitudinal edge 1184 of the distribution tip 1180 in image 1132. Other lines of the distribution tip 1180 may be used as reference lines.

[0735] At operation 1194, the image evaluation device 1122 is positioned at a predetermined offset 1186 from the reference line 1184. In some embodiments, the predetermined offset 1186 determines the horizontal position of the region of interest 1182, while the vertical position of the region of interest 1182 is preset to be a predetermined height 1188 from the bottom of the image 1132. In some embodiments, the vertical position of the region of interest remains approximately the same across different images because the image capture unit is repeatedly arranged at the sample height relative to the dispensing tip.

[0736] An example of the image processing method used above can be implemented using Cognex In-Sight Vision software, which is available from Cognex Corporation (Nartick, Massachusetts) and offers a variety of tools such as edge detection (“Edge”), pattern matching (“Pattern Match”), and histogram analysis (“Histogram”).

[0737] Figure 47 This is a flowchart of an example method 1210 for extracting color parameters from image 1132. See also... Figure 48 Method 1210 is described, and the figure illustrates an exemplary histogram 1220 of image 1132. In some embodiments, method 1210 includes operations 1212 and 1214.

[0738] At operation 1212, image evaluation device 1122 generates a histogram 1220 for image 1132. In some embodiments, histogram 1220 is generated from data of regions of interest 1182 in image 1132. In some embodiments, there is more than one region of interest; therefore, image evaluation device 1122 generates a histogram 1120 for each region of interest in image 1132. For example, if there are three regions of interest in image 1132, image evaluation device 1122 generates three corresponding histograms.

[0739] like Figure 48 As shown, histogram 1220 represents the distribution of different colors in image 1132 (e.g., its region of interest 1182). In some embodiments, histogram 1220 shows the number of pixels with color in each range of a fixed list of color ranges (also referred to herein as intervals). Histogram 1220 can be constructed for any type of color space. In the illustrated example, the RGB color model is used. In other embodiments, the CMYK color model and any other color model can be used.

[0740] A histogram 1220 can be generated by first discretizing the colors in image 1132 (i.e., red, green, and blue in the RGB model) (e.g., its region of interest 1182) into multiple intervals and counting the number of pixels in each interval. For example, if image 1132 is an 8-bit image, the values ​​of 0 to 255 for each color are grouped into multiple intervals, such that each interval includes a range of ten values. For example, the first interval includes values ​​equal to or greater than zero and less than 10, the second interval includes values ​​equal to or greater than 10 and less than 20, and the third interval includes values ​​equal to or greater than 20 and less than 30. Figure 48 As shown, histogram 1220 depicts a first color channel 1222, a second color channel 1224, and a third color channel 1226, which represent the red, green, and blue components in the RGB model, respectively. In other embodiments, different color components from the RGB model, CMYK color model, or any other color model can be used. In other embodiments, the image can be of different bit sizes, such as 15-bit color, 16-bit color, 24-bit color, 30-bit color, 36-bit color, 48-bit color, or any other bit value.

[0741] At operation 1214, the image evaluation device 1122 obtains multiple color parameters 1220 from the histogram 1134. In some embodiments, the image evaluation device 1122 generates six color parameters. For example, the first color parameter 1232 is the mean of the first color channel 1222, the second color parameter 1234 is the mean of the second color channel 1224, and the third color parameter 1236 is the mean of the third color channel 1226. Furthermore, the fourth color parameter 1242 is the Riemann sum of the first color channel 1222, the fifth color parameter 1244 is the Riemann sum of the second color channel 1224, and the sixth color parameter 1246 is the Riemann sum of the third color channel 1226. The Riemann sums of the first color channel 1222, the second color channel 1224, and the third color channel 1226 represent the areas under the curves of the first color channel 1222, the second color channel 1224, and the third color channel 1226, respectively.

[0742] In other implementations, other color parameters are generated from histogram 1220. For example, the color parameters may include the maximum value of the first color channel 1222, the maximum value of the second color channel 1224, the maximum value of the third color channel 1226, the minimum value of the first color channel 1222, the minimum value of the second color channel 1224, the minimum value of the third color channel 1226, the mode of the first color channel 1222, the mode of the second color channel 1224, the mode of the third color channel 1226, the histogram header of the first color channel 1222, the histogram header of the second color channel 1224, and the histogram header of the third color channel 1226. The histogram header of color channel 1226, the histogram tail of color channel 1222, the histogram tail of color channel 1224, the histogram tail of color channel 1226, the percentage of the histogram header of color channel 1222, the percentage of the histogram header of color channel 1224, the percentage of the histogram header of color channel 1226, the percentage of the histogram tail of color channel 1222, the percentage of the histogram tail of color channel 1224, and the percentage of the histogram tail of color channel 1226. The histogram header specifies the minimum grayscale value of the histogram. For example, the histogram header of color channel 1222 specifies the minimum grayscale value of color channel 1226 in the histogram. The histogram tail specifies the maximum grayscale value of the histogram. For example, the histogram tail of color channel 1222 specifies the maximum grayscale value of color channel 1226 in the histogram. The histogram header percentage specifies the percentage of total pixels in the histogram that exist within a specified range of gray values ​​with the lowest gray value. For example, the histogram header percentage for first color channel 1222 specifies the percentage of total pixels in the histogram for first color channel 1222 that exist within the lowest range of gray values ​​in first color channel 1222. The histogram tail percentage specifies the percentage of total pixels represented in the histogram that exist within a specified range of gray values ​​with the highest gray value. For example, the histogram tail percentage for first color channel 1222 specifies the percentage of total pixels in the histogram for first color channel 1222 that exist within the highest range of gray values ​​in first color channel 1222.

[0743] In other embodiments, color parameters include the mean of color channels (e.g., first, second, and third color channels), the peak value of color channels (e.g., first, second, and third color channels), and / or the standard deviation of color channels (e.g., first, second, and third color channels). In other embodiments, other types of color parameters are used.

[0744] Figure 49 It is used for operation Figure 42 A flowchart illustrating an exemplary method 1270 of the classification data generation apparatus 1124. (Refer to...) Figure 50 and Figure 51Method 1270 is described. Figure 50 This is an example table 1278 showing how interference values ​​are parsed into classification labels. Figure 51 It can be used as a source Figure 42 An exemplary set of sample classification identifiers 1310 output by the classification device 1126.

[0745] In some implementations, as described below, different levels of sample quality are categorized into multiple target variables, also referred to herein as sample classification identifiers. Specifically, classification device 1126 determines the sample quality as one of the sample classification identifiers. Classification data generation device 1124 is used to generate sample classification identifiers for specific interfering substances or groups of specific interfering substances. In some implementations, sample classification identifiers are constructed by first resolving the interfering substance values ​​of a specific sample into a set of labels based on the concentration values ​​of each interfering substance. The interfering substance labels are then combined into a set of labels (i.e., sample classification identifiers) that classify the range of all interfering substances in the sample.

[0746] See still Figure 49 At operation 1272, the classification data generation device 1124 defines the concentration value of each interfering substance. For example, Figure 50 As shown, three interfering substances were evaluated for the sample 1130 aspirated at the dispensing tip: a first interfering substance 1280, a second interfering substance 1282, and a third interfering substance 1284. Concentration values ​​1290, 1292, and 1294 were defined for interfering substances 1280, 1282, and 1284, respectively. In some embodiments, the concentration values ​​are defined as one or more discrete concentration values. In other embodiments, the concentration values ​​are defined as a range of concentration values.

[0747] For example, three concentration values ​​1290 (e.g., value 1-1, value 1-2, and value 1-3) are defined for a first interfering substance 1280, three concentration values ​​1292 (e.g., value 2-1, value 2-2, and value 2-3) are defined for a second interfering substance 1282, and three concentration values ​​1294 (e.g., value 3-1, value 3-2, and value 3-3) are defined for a third interfering substance 1284. In other embodiments, other numbers of concentration values ​​are defined for the same or different interfering substances.

[0748] At operation 1274, the classification data generation device 1124 assigns classification labels 1300, 1302, and 1304 to concentration values ​​1290, 1292, and 1294. In the same example, the concentration value 1290 of the first interfering substance 1280 is assigned three classification labels 1300, such as ZERO, MEDIUM, and HIGH. The concentration value 1292 of the second interfering substance 1282 is assigned two classification labels 1302, such as ABSENT and PRESENT. The concentration value 1294 of the third interfering substance 1284 is assigned three classification labels 1304, such as ZERO, MEDIUM, and HIGH. Other implementations of the classification labels are also possible. For example, in other implementations, the concentration value 1292 of the second interfering substance 1282 may be assigned three classification labels, such as ZERO, MEDIUM, and HIGH, similar to the three classification labels 1300 and 1304. In other embodiments, concentration values ​​1290 and 1294 can be assigned classification labels such as ABSENT and PRESENT, similar to the two classification labels 1302.

[0749] At operation 1276, the classification data generation device 1124 generates a list of sample classification identifiers 1310 based on different combinations of interfering substance concentration values. The sample classification identifiers 1310 are used to approximate the content or concentration of all considered combinations of interfering substances. As described below, the sample classification identifiers 1310 are used as a target variable of the classification device 1126 or as an output from the classification device 1126.

[0750] like Figure 51 As shown, the list of sample classification identifiers 1310 includes all possible combinations of classification labels 1300, 1302, and 1304. An exemplary notation for the sample classification identifier 1310 is a combination of classification label 1300 for the first interfering object 1280, classification label 1302 for the second interfering object 1282, and classification label 1304 for the third interfering object 1284, in sequence. In the illustrated example, since the first interfering object 1280 has three classification labels (e.g., ZERO, MEDIUM, and HIGH), the second interfering object 1282 has two classification labels (e.g., ABSENT and PRESENT), and the third interfering object 1284 has three classification labels (e.g., ZERO, MEDIUM, and HIGH), there can be 18 (=3×2×3) sample classification identifiers 1310. The sample classification identifier is also referred to herein as a sample classifier. Other sample classification identifiers are also possible. For example, the second interfering object 1282 may have three classification labels (e.g., ZERO, MEDIUM, and HIGH) instead of two classification labels (e.g., ABSENT and PRESENT).

[0751] Figure 50An example of color parameter data table 1320 for a mixture of three interfering substances is shown, each interfering substance having five values. In the example shown, the first interfering substance 1280 is hemoglobin, the second interfering substance 1282 is jaundice (bilirubin), and the third interfering substance 1284 is hyperlipidemia (lipids), where instrument 100 is an immunoassay analyzer. By way of example, the first interfering substance 1280 is divided into three segments with five values, such as 0 mg / dL for value 1-1 of classification label 1300 ZERO, 250 and 500 mg / dL for value 1-2 of classification label 1300 MEDIUM, and 750 and 1000 mg / dL for value 1-3 of classification label 1300 HIGH. The second interfering agent 1282 is divided into three segments with five values, such as 0 mg / dL for value 2-1 of classification label 1302 as ABSENT, 10 and 20 mg / dL for value 2-2 of classification label 1302 as PRESENT, and 30 and 40 mg / dL for value 2-3 of classification label 1302 as PRESENT. In other embodiments, the second interfering agent 1282 may be divided into three segments with five values, such as 0 mg / dL for value 2-1 of classification label 1302 as ZERO, 10 and 20 mg / dL for value 2-2 of classification label 1302 as MEDIUM, and 30 and 40 mg / dL for value 2-3 of classification label 1302 as HIGH. The third interferon 1284 was divided into three segments with five values, such as 0 mg / dL for value 3-1 for ZERO of classification label 1304, 125 and 250 mg / dL for value 3-2 for MEDIUM of classification label 1304, and 375 and 500 mg / dL for value 3-3 for HIGH of classification label 1304.

[0752] Figure 53 The predictions are shown from, for example Figure 52 An exemplary set of sample classifiers 1310 output by a combination of the first, second, and third interfering factors is shown. Figure 53 The classifier 1310 in the example only shows those based on, such as Figure 52 The following are some possible outputs of the first, second, and third interfering devices. (See reference...) Figure 51The notation for creating sample classifier 1310 is as follows. For example, if a sample contains 0 mg / dL of lipids (“ZERO” in Table 1320), 10 mg / dL of jaundice (“PRESENT” in Table 1320), and 375 mg / dL of hemoglobin (“HIGH” in Table 1320), then sample classifier 1310 is designated as “ZeroPresentHigh”. Other sample classifiers 1310 are also possible. For example, if a sample contains 0 mg / dL of lipids (“ZERO” as the classification label), if the sample contains 10 mg / dL of jaundice, then it can have a classification label of “MEDIUM” instead of “PRESENT”, and if the sample contains 375 mg / dL of hemoglobin (“HIGH” as the classification label), then sample classifier 1320 will be designated as “ZeroMediumHigh”. For example, if a sample contains 0 mg / dL of lipids (“ZERO” as the classification label), if the sample contains 0 mg / dL of jaundice, it can have a classification label of “ZERO” instead of “ABSENT”, and if the sample contains 375 mg / dL of hemoglobin (“HIGH” as the classification label), then the sample classifier 1320 will be designated as “ZeroZeroHigh”. Figure 54 It is shown schematically. Figure 42 A block diagram of an example of the classification device 1126 is provided. As described above, the classification device 1126 is used to receive one or more of the color parameters 1134 and generate a sample classification result 1138. The classification device 1126 also receives classification data 1136 to generate the sample classification result 1138. In some embodiments, the classification device 1126 generates feedback data 1330. As described herein, the classification device 1126 is integrated into the instrument 100, eliminating the need for a separate device to assess sample quality.

[0753] In some embodiments, color parameter 1134 includes at least one of color parameters 1232, 1234, 1236, 1242, 1244, and 1246 as described above. In other embodiments, sorting device 1126 utilizes all color parameters 1232, 1234, 1236, 1242, 1244, and 1246. In other embodiments, sorting device 1126 uses other types of color parameters.

[0754] In some embodiments, the classification device 1126 processes the color parameter 1134 and selects one from the list of sample classification identifiers 1310 as the sample classification result 1138. The sample classification result 1138 includes one of the sample classification identifiers 1310, which typically indicates sample quality or integrity. Therefore, the output of the sample quality detection device 1112 is not a quantifiable number indicating the amount or concentration of interfering substances contained in the sample. Instead, the sample quality detection device 1112 outputs a classifier (i.e., a classification identifier), which is a simple indication of sample quality.

[0755] When a sample contains multiple considered interfering substances, these substances can cause spectral overlap, making it difficult to detect one interfering substance in relation to others. For example, when hemoglobin (red, etc.), bilirubin (yellow, etc.), and lipids (white, etc.) are interfering substances in a sample, the absorption of hemoglobin, bilirubin, and lipids overlaps at least partially, making it difficult to distinguish these interfering substances. Therefore, rather than outputting the specific amount or concentration of interfering substances, it is desirable to simplify sample quality results by using a sample classifier.

[0756] In some implementations, the classification device 1126 uses feedback data 1330 suitable for improving the operation of the classification device 1126. The feedback data 1330 may include information about the correlation between the input color parameter 1134 and the output sample classification result 1138. The feedback data 1330 is fed back and used to improve future operation by further training the classification device 1126.

[0757] In some implementations, the classification device 126 employs a machine learning model. For example, the classification device 126 uses a support vector machine (SVM) model, which is a supervised learning model that utilizes one or more relevant learning algorithms to analyze the data used for classification. Other models, such as logistic regression, neural networks, convolutional neural networks, and classification trees, may also be used in other implementations.

[0758] like Figure 54As shown, some implementations of the classification device 1126 perform training operation 1340 and normal operation 1342. In training operation 1340, the classification device 1126, employing an SVM training algorithm, builds a model from a set of training example samples, each labeled as belonging to one of the sample categories. The model assigns new examples to one category or another, making it a nonprobabilistic binary linear classifier. The SVM model represents examples as points in space, mapped such that examples of individual categories are separated by the widest possible explicit gap. New examples are then mapped to the same space and their category is predicted based on which side of the gap they fall into. As an alternative to linear classification, the SVM model can perform nonlinear classification using kernel methods (e.g., radial basis functions), mapping its input to a high-dimensional feature space. For example, the SVM model constructs hyperplanes or a set of hyperplanes in a high-dimensional or infinite-dimensional space, which can be used for classification. Hyperplanes that are furthest from the nearest training data point of any class achieve good separation because, in general, the larger the margin, the smaller the generalization error of the classifier.

[0759] In the example shown in this paper, a dimensional space for SVM is constructed from the RGB configuration described above, resulting in a six-dimensional predictor space corresponding to the six color parameters. As mentioned above, the target variable for classification is constructed by resolving the measured values ​​of interfering substances for each sample (e.g., hemoglobin, jaundice, and lipemia, collectively referred to as HIL in this paper) into a set of labels based on the concentration ranges for each HIL component. The sample labels for each interfering substance are combined into a single label, which is used to classify the ranges of all three HIL components. It is this overall sample classification label that serves as the target variable for the SVM classifier.

[0760] In some implementations, the SVM classifier is tuned using a hyperparameter called "nu," which regularizes the number of support vectors and the training error. For example, a classifier can be implemented in Python using the Sci-Kit Learn module, which has built-in support for Nu-regularized SVM classifiers (such as "sklearn.svm.NuSvc").

[0761] Once the SVM model is established in training operation 1340, the classification device 1126 is ready for normal operation 1342, where the quality of patient samples is assessed on-site for laboratory analysis in instrument 100. In some embodiments, the classification device 1126 is pre-trained before instrument 100 is installed at the customer's site. In other embodiments, the classification device 1126 continues to be updated with feedback data 1330 during normal operation 1342. In other embodiments, the classification device 1126 may be configurable by the customer.

[0762] Figure 55This is an example dataset 1350 containing sample classification results 1138 and associated labeling results 1352. (Example dataset 1350 is shown.) Figure 43 As shown, the sample integrity detection device 1112 generates a labeling result to indicate whether the aspirated sample 1130 has appropriate quality for subsequent processing. Figure 43 Operation 1162). For example... Figure 55 As shown, one or more of the sample classification results 1138 are considered to indicate that the associated sample does not have sufficient quality for laboratory analysis in instrument 100. Samples associated with such sample classification results 1138 can be labeled to indicate impaired sample quality. By way of example, dataset 1350 shows which sample classification results indicate samples that need to be labeled.

[0763] like Figures 42 to 55 As shown, the sample quality detection device 1112 is used to transform a complex variable space (associated with multiple color parameters) into a simple output (including a sample classifier) ​​representing sample quality. The output sample classification result 1138 is used to notify the user whether the sample has been properly prepared to have sufficient quality or integrity for laboratory analysis.

[0764] The sample quality inspection device 1112 can be modified to suit various applications. For example, the sample quality inspection device 1112 is suitable for any in vitro diagnostic analyzer, any sample tube or reaction reservoir, and any container shape. In some embodiments, the image evaluation device 1122 of the sample quality inspection device 1112 does not require the use of a predefined region of interest for image processing. The camera unit of the image capture device 1120 can be of any type or quality. According to an exemplary embodiment, the sample quality inspection device 1112 can use a consumer-grade camera unit, such as a camera accompanying a mobile device. The light source used in the image capture device 1120 can be located anywhere. In some embodiments, the classification device 1126 can be trained on-site at the customer's location. In other embodiments, the classification device 1126 can be tuned using a learning algorithm to adjust performance based on the unique population and interfering (e.g., HIL) values ​​of the customer's patient samples.

[0765] See Figures 56 to 68 An example of a tip alignment detection device 1114 is described.

[0766] Figure 56 This is a block diagram of an example of a tip alignment detection device 1114. The tip alignment detection device 1114 is used to detect misalignment of the dispensing tip 112 and correct the detection volume of liquid substance contained in the dispensing tip 112.

[0767] In some implementations, the image-based volume detection device 1500 is used to capture an image of the dispensing tip 112 after a liquid substance (such as a sample) has been aspirated, and to calculate the volume of the liquid substance based on the image of the dispensing tip 112. An example of the image-based volume detection device 1500 includes the dispensing tip volume detection device 400 as described herein. For example, as described herein, the sample aspiration device 152 is used to aspirate a sample into the dispensing tip 112, and the dispensing tip volume detection device 400 uses the dispensing tip image capture unit 130 to capture an image of the dispensing tip and calculates the volume of the aspirated sample by analyzing the captured image.

[0768] In some implementations, the detection volume of liquid substance (e.g., sample) in the dispensing tip 112 is not always accurate due to various sources of tolerance and misalignment, such as Figure 57 and 58 As stated in the text. Therefore, there is some error in detecting volume 1502.

[0769] Tip alignment detection device 1114 is used to detect at least the misalignment of dispensing tip 112 relative to sample aspiration module 512 and / or dispensing tip image capture unit 130. Misalignment of dispensing tip 112 results in an error in detecting the volume of sample aspirated into dispensing tip 112. Tip alignment detection device 1114 is used to correct the volume of substance detected by image-based volume detection device 1500 (e.g., dispensing tip volume detection device 400) and provide a corrected volume of aspirated substance 1504.

[0770] As described herein, the tip alignment detection device 1114 and the image-based volume detection device 1500 may be part of the instrument 100 and thus operate together with the systems, devices, components, engines and other components of the instrument 100 as described herein.

[0771] Figure 57 This is a cross-sectional view of an example of a dispensing tip 112, illustrating possible tolerances in the configuration of the dispensing tip 112. The dispensing tip 112 is designed to have permissible tolerances in one or more dimensions. Some of these dimensions include lengths L10, L11, and L12, and widths or diameters D10, D11, and D12. The tolerances allowed for the dispensing tip 112 can affect the volume of material contained within the dispensing tip 112.

[0772] Figure 58An exemplary misalignment of the dispensing tip 112 is schematically illustrated. As shown, when the dispensing tip 112 (also referred to herein as 112) engages with the sample aspiration module 512 (such as its mandrel 528), the dispensing tip 112 is not always positioned as required. In some embodiments, it may be desirable for the dispensing tip 112 to be positioned vertically or aligned with the mandrel 526. However, the dispensing tip 112 may be tilted relative to the mandrel 526, and the volume of the substance 540 may be observed from a different perspective than that of the dispensing tip image capture unit 130. Therefore, misalignment of the dispensing tip 112 may affect the accuracy of detecting the volume of the substance 540 aspirated into the dispensing tip 112.

[0773] Figure 59 Possible types of misalignment of the dispensing tip 112 are shown. Figure 1 The position of the distribution tip 112 relative to the camera unit of the distribution tip image capture unit 130 is shown. While the Z-axis is defined as the axis along which the distribution tip 112 typically extends, the X-axis is defined as the direction along which the distribution tip 112 can tilt from left to right or from right to left relative to the camera unit of the distribution tip image capture unit 130, as shown in the diagram. Figure 2 As shown. When the dispensing tip 112 is tilted in the X-axis direction, the misalignment can be represented by the lateral misalignment angle C, as shown in the figure. Figure 2 As shown (“side misalignment”). The Y-axis is defined as the direction in which the distribution tip 112 can tilt away from or towards the camera unit, as shown in the diagram. Figure 3 As shown. When the dispensing tip 112 is tilted in the Y-axis direction, the misalignment can be represented by the depth misalignment angle D, as shown in the figure. Figure 3 As shown (“depth misalignment”). This depth misalignment is not recognized from the two-dimensional image captured by the tip image capture unit 130.

[0774] Figure 60A This is a cross-sectional side view of an exemplary dispensing tip 1510 configured for use with a tip alignment detection device 1114. In this example, the dispensing tip 1510 is aligned with, as referenced... Figure 13 and 14 The dispensing tip 112 is similarly configured. Therefore, the description of the dispensing tip 1510 is mainly limited to the differences from the dispensing tip 112, and other descriptions are omitted for brevity.

[0775] In this example, the assignment tip 1510 includes a first reference line 1512 and a second reference line 1514, as follows: Figure 60B And better shown in 60C (they are) Figure 60A(An unfolded view of some portions of the dispensing tip). In some embodiments, the first reference line 1512 and the second reference line 1514 are used to detect lateral misalignment of the dispensing tip, as shown in the reference diagram. Figure 62 As described above. Furthermore, at least one of the first reference line 1512 and the second reference line 1514 is used to detect depth misalignment of the dispensing tip, such as... Figure 62 As stated above.

[0776] In some embodiments, reference lines 1512 and 1514 are configured to be detectable by the dispensing tip image capture unit 130. Reference lines 1512 and 1514 may be formed at various locations on the dispensing tip 1510. In some embodiments, the first reference line 1512 is positioned such that the surface or meniscus of the aspirated material is disposed below the first reference line 1512 (i.e., between the first reference line 1512 and the distal end 562 of the dispensing tip 1510). In other embodiments, the first reference line 1512 is positioned such that the meniscus of the aspirated fluid material is disposed above the first reference line 1512 relative to the distal end 562 (i.e., between reference line 570 and the proximal end 560). In some embodiments, the first reference line 1512 corresponds to... Figure 13 The reference line shown is 570.

[0777] The second reference line 1514 may be arranged relative to the first reference line 1512, close to the distal end 562 of the dispensing tip 1510. By way of example, the first reference line 1512 is positioned such that the surface line of 100 μL of aspirated material is disposed below the first reference line 1512 (i.e., between the first reference line 1512 and the distal end 562 of the dispensing tip 1510), while the second reference line 1514 is positioned such that the surface line of 2 μL of aspirated material is disposed above the second reference line 1512 (i.e., between the first reference line 1512 and the second reference line 1514).

[0778] The first reference line 1512 and the second reference line 1514 are provided to the dispensing tip 1510 in various ways. In some embodiments, the reference line is a detectable structure, such as a protrusion, ridge, recess, notch, or any other visible element formed on the dispensing tip. In other embodiments, the reference line is a mark or indicator applied or attached to the dispensing tip. The reference line may be integrally formed or molded to the dispensing tip. Alternatively, the reference line may be manufactured separately and attached to the dispensing tip.

[0779] Figure 61This is a flowchart illustrating an exemplary method 1550 for evaluating the alignment of assigned tips. In some embodiments, method 1550 is performed by a tip alignment detection device 1114. In other embodiments, other parts of instrument 100 may perform method 1550 together with or in lieu of the tip alignment detection device 1114.

[0780] At operation 1552, instrument 100 (such as sample aspiration system 510) is designed to aspirate fluid material (such as a sample) into dispensing tip 1510.

[0781] At operation 1554, instrument 100 (such as sample aspiration system 510) transports a dispensing tip 1510 containing the aspirated sample to dispensing tip image capture unit 130. In some embodiments, dispensing tip image capture unit 130 is arranged to capture an image of the dispensing tip after aspiration without transport. Dispensing tip image capture unit 130 then captures an image of dispensing tip 1510. In some embodiments, the image of dispensing tip 1510 is a digital image of a predetermined resolution.

[0782] At operation 1556, instrument 100, such as image-based volume detection device 1500 (e.g., dispensing tip volume detection device 400 or sample aspiration volume detection device 500, such as...) Figure 9 As shown), the volume of material in the dispensing tip 1510 is detected by analyzing the captured image. References have been made to, for example... Figures 16 to 19 An example of operation 1556 is described.

[0783] At operation 1558, instrument 100, such as tip alignment detection device 1114, uses captured images to detect misalignment of the assigned tip 1510. (See reference...) Figures 62 to 68 An example of operation 1558 is described.

[0784] At operation 1560, instrument 100 (such as tip alignment detection device 1114) is used to correct the volume of the detection (as detected in operation 1556) based on the detection of misalignment (as detected in operation 1558).

[0785] Figure 62 This is a flowchart illustrating an exemplary method 1570 for detecting misalignment of the dispensing tip. In this method, the tip alignment detection device 1114 can detect, for example... Figure 59 The points Figure 2 The depicted side is misaligned (at operation 1572), and as... Figure 59 The points Figure 3 The depicted depth is misaligned (at operation 1574).

[0786] Figure 63This is a flowchart illustrating another exemplary method 1600 for detecting misalignment of the dispensing tip. Also refer to... Figure 64 Method 1600 is described, and the figure schematically shows an exemplary image of misalignment of the sides of the dispensing tip.

[0787] In this method, operations 1602, 1604, 1606, 1608, 1610, 1612, and 1614 can be used to detect lateral misalignment. Operations 1602, 1622, 1624, and 1626 can be used to detect depth misalignment. In some embodiments, lateral misalignment can be detected as a portion of the volume detection process performed, for example, by the dispensing tip volume detection device 400 or the sample aspiration volume detection device 500 as described herein. For example, operations 1602, 1604, 1606, 1608, and 1616 are the same as or similar to some operations performed by the dispensing tip volume detection device 400 or the sample aspiration volume detection device 500, and therefore can be replaced by these operations of the dispensing tip volume detection device 400 or the sample aspiration volume detection device 500.

[0788] At operation 1602, the tip alignment detection device 1114 acquires an image of the assigned tip 1510. The assigned tip image capture unit 130 can capture the image of the assigned tip 1510.

[0789] At operation 1604, the tip alignment detection device 1114 detects a predetermined point 1640 on the first reference line 1512 of the dispensing tip 1510. In some embodiments, the predetermined point 1640 is the center of the first reference line 1512. Other points on the first reference line 1512 may be used in other embodiments.

[0790] At operation 1606, the tip alignment detection device 1114 detects a predetermined point 1642 on the meniscus 1632 of the fluid substance 1630 contained in the dispensing tip 1510. In some embodiments, the predetermined point 1642 is the center of the meniscus of the substance in the dispensing tip. Other points on the meniscus may be used in other embodiments.

[0791] In other embodiments, a second reference line 1514 is used instead of the meniscus of the fluid substance. In this application, the tip alignment detection device 1114 detects a predetermined point (e.g., the center) of the second reference line to which the tip is assigned.

[0792] At operation 1608, the tip is aligned with the connection points 1640 and 1642 of the detection device 1114 to define a straight line 1634 between points 1640 and 1642.

[0793] At operation 1620, the tip alignment detection device 1114 determines the angle C of the straight line 1634 relative to the reference line 1636. In some embodiments, the reference line 1636 is parallel to a vertical line in the image captured by the tip image capture unit 130. In other embodiments, other lines may be used as the reference line 1636.

[0794] Although the first reference line 1512 and the meniscus 1632 of the aspirated material 1630 are used to define the straight line 1634, other reference lines or points can be used to define the straight line 1634. For example, any combination of the first reference line 1512, the second reference line 1514, the meniscus 1632 of the aspirated material, other portions of the dispensing tip 1510, and any portion of the sample transfer module 512 that engages with the dispensing tip 1510.

[0795] At operation 1612, the tip alignment detection device 1114 determines whether angle C is less than a threshold. This threshold represents the maximum acceptable angle at which the dispensing tip can tilt. When the dispensing tip is tilted at an angle greater than the threshold angle value, the detected volume of material is considered unacceptable for obtaining reliable results. In some embodiments, the threshold angle value ranges from about 0.5 to about 5 degrees. In other embodiments, the threshold angle value ranges from about 1 to about 3 degrees. In other embodiments, the threshold angle value is about 2 degrees.

[0796] If the angle C of line 1634 is determined to be less than a threshold angle value ("Yes" is selected in this operation), method 1600 continues at operation 1616. Otherwise ("No" is selected in this operation), method 1600 proceeds to operation 1614, in which the tip alignment detection device 1114 marks the aspiration to indicate that the volume aspirated into the dispensing tip is not suitable for subsequent processes. At operation 1614, another aspiration can be performed using another dispensing tip to repeat operation 1602 and subsequent operations.

[0797] At operation 1616, the volume of material in the dispensing tip is obtained using a captured image. In some embodiments, the dispensing tip volume detection device 400 or the sample aspiration volume detection device 500 may perform this operation as described herein.

[0798] At operation 1618, the tip alignment detection device 1114 determines whether the detected volume is greater than a threshold volume value. The threshold volume value represents the maximum volume in the dispensing tip that may be affected (or significantly affected) by lateral misalignment and / or depth misalignment. When the volume of material contained in the dispensing tip is greater than this threshold, it is considered that lateral misalignment and depth misalignment do not significantly affect volume detection in the dispensing tip, and the calculation of such volume in the dispensing tip is acceptable regardless of whether there is lateral or depth misalignment. When the volume of material contained in the dispensing tip is equal to or less than this threshold, it is considered that lateral or depth misalignment can significantly affect volume detection based on the captured image, and the calculation of such volume is unacceptable.

[0799] In some embodiments, the threshold volume value ranges from about 3 to about 30 μL. In other embodiments, the threshold volume value ranges from about 5 to about 20 μL. In still other embodiments, the threshold volume value is about 10 μL.

[0800] If the detected volume is determined to be greater than the threshold volume value ("Yes" is selected at this operation), method 1600 continues at operation 1620, where the calculated volume is reported. Otherwise ("No" is selected at this operation), method 1600 proceeds to operation 1622 and subsequent operations.

[0801] At operation 1622, the tip alignment detection device 1114 is used to correct the detected volume using the second reference line 1514. (Reference) Figure 65 and 66 An exemplary method for correcting volume using a second reference line is described.

[0802] In the illustrated example, the primary description is that if the angle does not meet a threshold angle value, aspiration already performed on the dispensing tip is marked. Alternatively, method 1600 can be performed before aspirating a specific substance (such as a reagent, sample, or substrate) into the dispensing tip. In this configuration, if the angle does not meet the threshold angle value, the tip alignment detection device 1114 can be used to prevent the intended substance from being aspirated into the dispensing tip, or to generate a notification that aspiration of such intended substance should not be performed or should be performed with caution.

[0803] Figure 65 This is a flowchart illustrating an exemplary method 1650 for volume correction using a second reference line. Method 1650 can begin at operation 1652, where the tip alignment detection device 1114 obtains an image of the assigned tip 1510, such as... Figure 63 The operation is similar to 1602.

[0804] At operation 1654, the tip is aligned with the detection device 1114 to measure the length of the second reference line 1514 in the captured image.

[0805] At operation 1656, the tip alignment detection device 1114 calculates the ratio between the measured length of the second reference line 1514 and the actual length of the second reference line 1514. The actual length of the second reference line 1514 is known. For example, the actual length of the second reference line 1514 can be measured from an actual model or product of the dispensing tip 1510, or from an image of misalignment of the dispensing tip 1510.

[0806] The length of the second reference line 1514, measured from the captured image, will differ from that when the distribution tip 1510 is tilted in the Y direction (e.g., ...). Figure 59 The points Figure 3 (As shown) The actual length of the second reference line 1514. Therefore, the ratio between the measured length and the actual length of the second reference line 1514 can indicate the degree of depth misalignment occurring in the dispensing tip (i.e., the dispensing tip, as shown) Figure 59 In the middle Figure 3 How much would it tilt in the Y direction?

[0807] At operation 1658, the tip alignment detection device 1114 is used to correct the detected material volume using this ratio. Since the ratio between the measured length and actual length of the second reference line 1514 is related to the degree of depth misalignment of the dispensing tip, this ratio is also related to the material volume detected from the captured image. Therefore, this ratio can be used to adjust the volume of material in the dispensing tip estimated from the captured image.

[0808] Although the use of the second reference line 1514 in operations 1652, 1654, 1656, and 1658 has been primarily described, other reference lines or points can be used for the same operations. For example, the second reference line 1514 can be replaced by the first reference line 1512 or other features in the distribution tip 1510.

[0809] In the illustrated example, the primary description focuses on the ratio between the measured length of the second reference line 1514 and its actual length, used to adjust the measured volume. However, in another embodiment, method 1650 can be performed before aspirating a specific substance (e.g., a reagent, sample, or substrate) into the dispensing tip. In this application, if the ratio does not meet a predetermined threshold, the tip alignment detection device 1114 can be used to prevent the intended substance from being aspirated into the dispensing tip, or to generate a notification that aspiration of such intended substance should not be performed or should be performed with caution.

[0810] Figure 66 This is a flowchart illustrating another exemplary method 1670 for correcting volume using a second reference line. Also refer to... Figure 67Method 1650 is described, and the figure schematically illustrates the depth misalignment of the distribution tip relative to the camera unit.

[0811] In method 1670, operations 1672, 1674, and 1676 are... Figure 65 Operations 1652, 1654, and 1656 are the same or similar, therefore, for the sake of brevity, the description of these operations is omitted.

[0812] At operation 1678, the tip alignment detection device 1114 calculates the depth angle D based on the ratio calculated in operation 1676. Figure 59 and Figure 67 The points Figure 3 The depth angle D represents the angle at which the distribution tip is tilted in the Y direction (i.e., the depth direction), and is related to this ratio.

[0813] At operation 1680, the tip alignment detection device 1114 calculates the line of interest E′ based on the depth angle D. The line of interest E′ represents a camera perspective line 1685 that connects the proximal end 1684 of the distribution tip to the center 1686 of the second reference line 1514 of the correctly aligned (i.e., aligned with vertical line 1687) distribution tip. The line of interest E′ extends vertically from the camera perspective line 1685 to the proximal end 1684 of the distribution tip.

[0814] In some implementation schemes, such as Figure 67 The line E and angle D′ are shown to calculate the line of interest E′. In some embodiments, angle D′ may be approximated to depth angle D, where angles D′ and D are relatively small. Line E is a line extending between the proximal end 1684 of the distribution tip and the camera perspective line 1688. The camera perspective line 1688 extends from the center 1689 of the second reference line 1514 of the camera and the misaligned distribution tip 1690 (i.e., misaligned with depth angle D). Thus, the line of interest E′ corresponds to an adjustment or compensation to the line E obtained from the misaligned distribution tip.

[0815] In some implementation schemes, such as Figure 67 As shown, the tip alignment detection device 1114 includes or utilizes a camera unit 2550, which is included in the tip image capture unit 130. Figure 10 ).like Figure 2As shown, camera unit 2550 is mounted on sample precision suction and transfer unit (“sample precision gantry”) 152B. As described above, the configuration of camera unit 2550 and its associated components is similar to that of camera unit 550 and its associated components (e.g., light source 551, light source 552, and screen 553). An example of camera unit 2550 is an AE3-IS machine vision camera + I / O board, such as part number AE3-IS-CQBCKFP2-B purchased from Cognex Corporation (Nartick, MA).

[0816] At operation 1682, the tip-aligned detection device 1114 adjusts the detected volume based on the line of interest E′.

[0817] Figure 68 This is an exemplary data table 1694 showing volume detection before and after calibration performed by the tip alignment detection device 1114. In Table 1694, the second column shows the detected volume of material aspirated into the dispensing tip before calibration, and the third column shows the volume of material after calibration using the tip alignment detection device 1114.

[0818] See Figures 69 to 79 This describes an example of a particle concentration detection system 124.

[0819] Figure 69 yes Figure 1 A block diagram of an example particle concentration monitoring system 124. In some embodiments, particle concentration monitoring system 124 includes a reaction reservoir particle concentration monitoring system 1700.

[0820] The reaction reservoir particle concentration detection system 1700 is used to determine the particle concentration in a fluid substance contained in a reaction reservoir. In other embodiments, the reaction reservoir particle concentration detection system 1700 can also be used to detect particle concentration in other types of reservoirs, such as sample reservoirs, diluent reservoirs, and colorimetric tubes, which are used throughout the instrument 100. In some embodiments, the reaction reservoir particle concentration detection system 1700 uses a reservoir image capture unit 132 as described herein.

[0821] In clinical diagnostic applications, the binding-free mechanism of paramagnetic particles is often used to generate specific signals. However, due to certain tolerances, particles of varying sizes can be retained, making it difficult to achieve consistent particle retention rates across one or more cleaning steps. Several factors can influence particle loss during cleaning. Examples of these factors include dispensing tip alignment, reaction reservoir positioning, and variations in resuspension rotation speed. However, these factors cannot be precisely monitored.

[0822] like Figure 4As described above, an exemplary method for measuring particle concentration or particle retention is to use labeled paramagnetic particles (e.g., alkaline phosphatase) as a tool to directly measure the particles remaining after washing. Assuming that the signals (such as light) generated by the labeled paramagnetic particles are proportional to the amount of particles, these signals are measured to estimate the particle concentration. However, this method may require the enzyme reaction to take some time (e.g., at least about 5 minutes) to obtain results. The method also requires comparing results after a single wash with results after two washes to calculate the loss of paramagnetic particles for each wash. Providing diagnostic tools incurs additional costs, such as the provision of labeled particles. Alkaline phosphatase activity and binding capacity do not persist for a longer period, thus requiring the study and definition of a stationary period.

[0823] The Reactor Container Particle Concentration Inspection System 1700 is used to identify particle retention rates by analyzing images of the reaction container. The System 1700 can generate calibration data on-site by introducing different concentrations of particles into the reaction container.

[0824] As described herein, the reaction reservoir particle concentration monitoring system 1700 is part of instrument 100, and therefore instrument 100 operates together with the systems, devices, components, engines and other components described herein.

[0825] Figure 70 An exemplary image of a reaction reservoir 1701 with different particle concentrations is shown. The left image shows a reaction reservoir 1707 such as a colorimetric tube 320 ( Figure 4 ) and reaction reservoir 728 ( Figure 23 The fluid material 1708 in the image contains fewer particles than in the other images. The middle image shows that the fluid material in the reactor contains more particles than in the left image but fewer than in the right image. The right image shows that the fluid material in the reactor contains more particles than in the other images. As the paramagnetic particle concentration increases, the turbidity increases, and therefore the brightness changes accordingly. As the number of particles in the reactor increases, the number of photons generated from the backlight of the reactor and transmitted through the reactor decreases. Therefore, the brightness changes in the image of the reactor captured by the camera.

[0826] The brightness in the image of the reaction reservoir depends not only on the particle concentration in the reservoir but also on the camera exposure time. The optimal camera exposure time can be determined based on the type of measurement and the desired amount of particle concentration. Furthermore, the variability in particle concentration measurement varies with particle concentration. Therefor...

Claims

1. A system for evaluating fluid substances, the system comprising: A sample aspiration device configured to at least partially engage a dispensing tip, the sample aspiration device being configured to draw fluid material into the dispensing tip, the dispensing tip having at least one reference line; An image capture unit configured to capture an image of at least a portion of the dispensing tip; At least one computing device, the computing device being configured to: - Identify the at least one reference line of the distribution tip from the portion of the image of the distribution tip; - Determine at least one characteristic of the at least one reference line; as well as - Compare at least one characteristic of the at least one reference line with a threshold, the threshold representing the misalignment of the assigned tip.

2. The system of claim 1, wherein the at least one reference line comprises a first reference line and a second reference line formed on the dispensing tip.

3. The system according to any one of claims 1 to 2, wherein the at least one reference line comprises a first reference line and a second reference line formed on the dispensing tip; and The at least one computing device is further configured to: - Obtain the at least one property of the at least one reference line based on the following: - Determine the length of the first reference line; - Determine the length of the second reference line; and - Determine the angle of a straight line relative to at least one of a first reference line and a second reference line, the straight line connecting a predetermined point on the first reference line and a predetermined point on the second reference line; and - The misalignment of the distribution tip is determined based on at least one of the length of the first reference line, the length of the second reference line, and the angle of the straight line.

4. The system according to claim 1 or 2, wherein the system is configured to: In response to determining the misalignment, the sample aspiration device is prevented from drawing the fluid material into the dispensing tip.

5. The system according to claim 1 or 2, wherein the at least one computing device is further configured to: In response to determining the misalignment, a flag is set and / or an initiation is made to draw the fluid material into the dispensing tip.

6. The system according to claim 1 or 2, wherein the at least one computing device is further configured to: Identify at least one reference line of the distribution tip from the portion of the image of the distribution tip; Identify the surface layer of the fluid substance within the dispensing tip in the image; Determine the distance between the at least one reference line and the surface layer; as well as The volume of the fluid substance is determined by converting the distance into the volume of the fluid substance based on correlation data, which includes information about the correlation between the volume within the dispensing tip and the distances from the at least one reference line to a plurality of surface layers within the dispensing tip.

7. The system according to claim 6, The computing device is configured to determine the reference line based on pattern matching and / or segmentation of the captured image.

8. The system according to claim 6, The computing device is configured to search for a pattern representing the reference line in the captured image.

9. The system according to claim 6, The computing device is configured to compare at least a portion of the captured image with a reference image.

10. The system according to claim 9, The computing device is configured to determine the matching rate and / or correlation value between the portion of the captured image and the reference image.

11. The system according to claim 1 or 2, wherein the at least one reference line comprises a first reference line and a second reference line formed on the dispensing tip; The at least one computing device is further configured to: Determine the length of the first reference line in the image; Determine the length of the second reference line in the image; Determine the angle of a straight line relative to at least one of the first reference line and the second reference line; the straight line connects a predetermined point on the first reference line and a predetermined point on the second reference line; The misalignment of the dispensing tip is determined based on at least one of the length of the first reference line, the length of the second reference line, and the angle of the straight line; and The volume of the fluid substance is adjusted based on the determination of the misalignment.

12. The system of claim 1 or 2, wherein the misalignment of the dispensing tip includes lateral misalignment and depth misalignment.

13. The system according to claim 1 or 2, wherein the at least one reference line comprises a first reference line and a second reference line formed on the dispensing tip; and The at least one computing device is further configured to: Identify predetermined points of the first reference line in the image; Identify predetermined points of the second reference line in the image; Define an alignment line connecting the predetermined point of the first reference line and the predetermined point of the second reference line; Determine the angle of the alignment line relative to at least one of the first reference line and the second reference line; as well as The angle is compared with a threshold angle value, which indicates that the side of the dispensing tip is misaligned.

14. The system of claim 3, wherein the predetermined point of the first reference line is the center point of the first reference line in the image, and the predetermined point of the second reference line is the center point of the second reference line in the image.

15. The system of claim 13, wherein the system is configured to: In response to determining that the angle of the alignment line relative to at least one of the first reference line and the second reference line satisfies and / or exceeds the threshold angle value, the sample aspiration device is prevented from drawing the fluid material into the dispensing tip.

16. The system of claim 13, wherein the at least one computing device is further configured to: In response to determining that the angle of the alignment line relative to at least one of the first reference line and the second reference line satisfies and / or exceeds the threshold angle value, a flag is set to draw the fluid material into the dispensing tip and / or a flag is set to draw the fluid material into the dispensing tip.

17. The system according to claim 1 or 2, wherein the at least one computing device is further configured to: The length of the at least one reference line is determined based on the captured image of the tip; Obtain the actual length of the at least one reference line; Calculate the ratio between the length of the at least one reference line and the actual length of the at least one reference line; and The depth misalignment of the dispensing tip is determined based on the ratio.

18. The system of claim 17, wherein the system is further configured to: The determined volume of the fluid substance is adjusted based on the ratio.

19. The system according to claim 1 or 2, further comprising: Light source and sample transfer module, The light source and the image capture unit are attached to the sample suction module, and / or The light source and the image capture unit are configured to move together with the sample suction module, enabling the capture of an image of the dispensing tip at any position of the sample suction module.

20. The system according to claim 1 or 2, The sample aspiration device is configured to draw liquid into another dispensing tip; The system is configured to determine the volume of the liquid being drawn in; The image capture unit is configured to capture another image of the other distribution tip; The computing device is configured to determine the pixel distance between reference points in the image associated with the other distribution tip, and is configured to correlate the determined volume with the determined pixel distance.

21. The system according to claim 20, The computing device is configured to generate correlation data based on the determined volume and the determined pixel distance.

22. The system according to claim 21, The correlation data is generated based on multiple correlations between multiple determined pixel distances and multiple determined volumes of liquid drawn into the other dispensing tip.

23. The system according to claim 20, The aspirated liquid includes a dye solution; and / or The system is configured to determine the volume of the aspirated liquid based on spectrophotometry.

24. The system according to claim 20, The system is configured to determine the mass of the aspirated liquid and, based on the determined mass of the aspirated liquid, to determine the volume of the aspirated liquid.

25. A method for evaluating fluid substances in a container, the method comprising: The image capture unit is used to capture an image of at least a portion of the container; Using at least one computing device, a first reference line and a second reference line of the container are determined from the image of the container; Determine at least one characteristic of at least one of the first reference line and the second reference line. The at least one characteristic includes at least one of the following: the length of the first reference line; the length of the second reference line; And the angle of a certain straight line relative to at least one of the first reference line and the second reference line; The straight line connects a predetermined point on the first reference line and a predetermined point on the second reference line. as well as The at least one characteristic of at least one of the first reference line and the second reference line is compared with a threshold representing misalignment of the distribution tip.

26. The method according to claim 25, The first reference line and the second reference line are determined based on pattern matching and / or based on the segmentation of the captured image.

27. The method according to any one of claims 25 and 26, Determining the first reference line and the second reference line includes searching for patterns representing the first reference line and / or the second reference line in the captured image.

28. The method according to claim 25 or 26, Determining the first reference line and the second reference line includes comparing at least a portion of the captured image with a reference image.

29. The method of claim 28, further comprising: Determine the matching rate and / or correlation value between the portion of the captured image and the reference image.

30. The method of claim 25 or 26, wherein the container comprises a fluid substance, the method further comprising: Identify the surface layer of the fluid substance within the container in the captured image; Determine the distance between at least one of the first reference line and the second reference line and the surface layer; as well as The volume of the fluid substance is determined by converting the distance into the volume of the fluid substance based on correlation data, which includes information about the correlation between the volume within the container and the distance from at least one of the first reference line and the second reference line to multiple surfaces within the container.

31. The method according to claim 25 or 26, further comprising: Determine the length of the first reference line in the image; Determine the length of the second reference line in the image; Determine the angle of a straight line relative to at least one of the first reference line and the second reference line; the straight line connects a predetermined point on the first reference line and a predetermined point on the second reference line; The misalignment of the container is determined based on at least one of the length of the first reference line, the length of the second reference line, and the angle of the straight line; and The volume of the fluid substance is adjusted based on the determination of the misalignment.

32. The method of claim 25 or 26, wherein the misalignment of the container includes lateral misalignment and depth misalignment.

33. The method according to claim 25 or 26, further comprising: Identify predetermined points of the first reference line in the image; Identify predetermined points of the second reference line in the image; Define an alignment line connecting the predetermined point of the first reference line and the predetermined point of the second reference line; Determine the angle of the alignment line relative to at least one of the first reference line and the second reference line; as well as The angle is compared with a threshold angle value, which indicates that the side of the container is misaligned.

34. The method of claim 33, wherein the predetermined point of the first reference line is the center point of the first reference line in the image, and the predetermined point of the second reference line is the center point of the second reference line in the image.

35. The method of claim 33, further comprising: In response to determining that the angle of the alignment line relative to at least one of the first reference line and the second reference line satisfies and / or exceeds the threshold angle value, the fluid material is prevented from being drawn into the container.

36. The method of claim 33, further comprising: In response to determining that the angle of the alignment line relative to at least one of the first reference line and the second reference line satisfies and / or exceeds the threshold angle value, the pumping of the fluid material into the container is marked and / or the pumping of the fluid material into the container is initiated.

37. The method according to claim 25 or 26, further comprising: The length of at least one of the first reference line and the second reference line is determined based on the captured image of the container; Obtain the actual length of at least one of the first reference line and the second reference line; Calculate the ratio between the length of at least one of the first reference line and the second reference line and the actual length of at least one of the first reference line and the second reference line; as well as The container's depth misalignment is determined based on the ratio.

38. The method of claim 37, further comprising: The determined volume of the fluid substance is adjusted based on the ratio.

39. A computer program product, when executed on a computing device for evaluating a fluid substance, instructs the computing device to perform the steps of the method according to any one of claims 25 to 38.

40. A non-transitory computer-readable medium on which the computer program product of claim 39 is stored.

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