Substance preparation evaluation system

Abstract

To provide automatic substance preparation and evaluation.SOLUTION: Automatic substance preparation and evaluation systems and methods are provided for preparing and evaluating a fluidic substance 118, such as a sample with bodily fluid, in a container 110 and / or in a dispense tip 112. The systems and methods can detect volumes, evaluate integrities, and check particle concentrations in the container and / or the dispense tip. A method of evaluating a fluidic substance in a container comprises: capturing, using an image capture device, an image of at least a portion of the container; obtaining, using at least one computing device, a plurality of color parameters of at least a portion of the image; and generating a sample classification result for the fluidic substance contained in the container based on the plurality of color parameters; where the sample classification result is representative of a concentration of at least one interferent in the fluidic substance.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] (CROSS-REFERENCE TO RELATED APPLICATIONS) This application was filed as a PCT International patent application on October 27, 2017, and claims the benefit of priority to U.S. Provisional Patent Application No. 62 / 414,655, filed October 28, 2016, and U.S. Provisional Patent Application No. 62 / 525,948, filed June 28, 2017, the entire disclosures of which are incorporated herein by reference in their entireties.

[0002] FIELD OF THE INVENTION The present invention relates generally to the field of automated substance preparation and evaluation. Specifically, the present invention relates to methods and systems for evaluating fluidic substances, such as samples with bodily fluids in containers and / or dispensing tips. Furthermore, the present invention relates to computer program elements for instructing a computer device and / or a processing device to perform any steps of a method for evaluating a fluidic substance. The present invention also relates to computer-readable media storing such computer program elements. Summary of the Invention [Means for solving the problem]

[0003] It may be an object of the present invention to provide improved methods and systems for automatically assessing fluid materials with increased reliability, increased quality, increased accuracy, and increased throughput.

[0004] The object of the present invention is solved by the subject matter of the independent claims, further embodiments of which are incorporated into the dependent claims and the following description.

[0005] According to a first aspect of the present disclosure, a method for evaluating a fluidic substance in a container is provided. Among other things, the method according to the first aspect may refer to a method for operating a dispensing tip evaluation system such as that exemplarily described with reference to FIG. 1 and / or a method for operating a sample quality detection device such as that exemplarily described with reference to FIGS. 42-55. The method according to the first aspect may also refer to a method for operating a volume detection system such as that exemplarily described with reference to FIGS. 5-15 and / or 9-21. The method of the first aspect may also refer to a method for operating a correlation data generation system such as that exemplarily described with reference to FIGS. 8-21.

[0006] The method according to the first aspect comprises: capturing an image of at least a portion of the container using an image capture device, which may comprise an image capture unit; obtaining, using at least one computing device and / or at least one processing device, a plurality of color parameters of at least a portion of the image; generating a sample classification of the fluidic material contained in the container based on the plurality of color parameters; Includes. Therein, the sample classification result represents and / or indicates the concentration of at least one interfering substance in the fluid material. Here and below, image capture device and / or image capture unit may refer to, for example, a dispensing tip image capture unit.

[0007] According to an embodiment of the method of the first aspect, the step of obtaining a plurality of color parameters comprises: generating a histogram of at least a portion of an image, said histogram comprising a plurality of color channels; obtaining a plurality of averages and / or means of a plurality of color channels, wherein the plurality of color parameters comprises a plurality of averages of the plurality of color channels; Includes. Therein, the average and / or mean value may be determined for each of the color channels or for a subset of the color channels.

[0008] According to an embodiment of the method of the first aspect, the step of obtaining a plurality of color parameters comprises: generating a histogram of at least a portion of an image, said histogram comprising a plurality of color channels; obtaining and / or determining a plurality of Riemann sums of a plurality of color channels, wherein the plurality of color parameters comprises a plurality of Riemann sums of the plurality of color channels; Includes. Therein, a Riemann sum may be obtained and / or determined for each of the color channels or for a subset of the color channels.

[0009] According to an embodiment of the method of the first aspect, the step of obtaining a plurality of color parameters comprises: generating a histogram of at least a portion of an image, said histogram comprising a plurality of color channels; obtaining a plurality of modes for a plurality of color channels; obtaining multiple maxima of multiple color channels; and / or obtaining a plurality of minimum values of a plurality of color channels, wherein the plurality of color parameters include a plurality of modes, maximum values, and / or minimum values of the plurality of color channels; Includes.

[0010] According to an embodiment of the method of the first aspect, the step of obtaining a plurality of color parameters comprises: generating a histogram of at least a portion of an image, said histogram comprising a plurality of color channels; obtaining a plurality of histogram heads for a plurality of color channels; obtaining a plurality of histogram tails for a plurality of color channels; obtaining a plurality of histogram head ratios for a plurality of color channels; and / or obtaining a plurality of histogram tail ratios for a plurality of color channels, wherein the plurality of color parameters include a plurality of histogram heads, histogram tails, histogram head ratios, and / or histogram tail ratios for the plurality of color channels; Includes.

[0011] According to an embodiment of the method of the first aspect, the plurality of color parameters include at least one of a plurality of means of the color channels, a plurality of Riemann sums of the color channels, a plurality of modes of the color channels, a plurality of maxima of the color channels, a plurality of minima of the color channels, a plurality of histogram heads of the color channels, a plurality of histogram tails of the color channels, a plurality of histogram head ratios of the color channels, a plurality of histogram tail ratios of the color channels, or any combination of the foregoing.

[0012] According to an embodiment of the method of the first aspect, the multiple color channels include a red component, a green component, and a blue component, for example in the RGB model, although any other type of color model may also be used, such as, for example, the CMYK color model.

[0013] According to an embodiment of the method of the first aspect, the sample classification result comprises at least one classification identifier, the at least one classification identifier being correlated with at least a portion of the plurality of color parameters and / or being correlated with the concentration of at least one interfering substance in the fluid material.

[0014] According to an embodiment of the method of the first aspect, the method further comprises generating a flagging result based on the sample classification result, the flagging result indicating the quality of the fluid material. Alternatively or additionally, the quality of the fluid material is based on the sample qualification result.

[0015] According to an embodiment of the method of the first aspect, the at least one interfering substance is one or more selected from hemoglobin, icterus, and lipemia.

[0016] According to an embodiment of the method of the first aspect, the container is a dispensing tip configured to aspirate a fluidic substance and / or a sample.

[0017] According to an embodiment of the method of the first aspect, the image capture device is configured and / or arranged to capture an image of the portion of the fluidic material and / or the container from a side of the container.

[0018] According to an embodiment of the method of the first aspect, the method further comprises: using at least one computing device to identify and / or determine a reference point in the image, the reference point being associated with the container; using at least one computing device to identify and / or determine a surface level of the fluidic material within the container in the image; Determining and / or measuring the distance between a reference point and a surface level; converting the distance to a volume of the fluid material based on correlation data, the correlation data including information about the correlation between the volume within the container and the distance from a reference point to a plurality of surface levels within the container; Includes. However, it should be noted that the term "correlation data" may also refer to an equation and / or a functional relationship between distance and volume.

[0019] According to an embodiment of the method of the first aspect, the distance is measured by pixel distance.

[0020] According to an embodiment of the method of the first aspect, the container is a dispensing tip configured to aspirate a fluidic substance, and 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.

[0021] According to an embodiment of the method of the first aspect, the reference lines are identified based on pattern matching and / or based on segmentation of the captured images.

[0022] According to an embodiment of the method of the first aspect, identifying the reference lines comprises searching for a pattern in the captured image that is representative of the reference lines.

[0023] According to an embodiment of the method of the first aspect, identifying the reference line comprises comparing at least a portion of the captured image to a reference image.

[0024] According to an embodiment of the method of the first aspect, the method further comprises determining a match rate, a match score, and / or a correlation value of the portion of the captured image and the reference image.

[0025] According to an embodiment of the method of the first aspect, the method further comprises: providing the liquid to a further container; determining the volume of liquid dispensed; capturing a further image of the container; determining pixel distances between reference points in the image associated with the further container; correlating the determined volume with the determined pixel distance; Includes.

[0026] According to an embodiment of the method of the first aspect, the method further comprises generating correlation data based on the determined volume and the determined pixel distance.

[0027] According to an embodiment of the method of the first aspect, the correlation data is generated based on a plurality of correlations between a plurality of determined pixel distances and a plurality of determined volumes of liquid to be dispensed into the further container.

[0028] According to an embodiment of the method of the first aspect, the dispensed liquid comprises a dye solution. Alternatively or additionally, the volume of the dispensed liquid is determined spectrophotometrically.

[0029] According to an embodiment of the method of the first aspect, determining the volume of dispensed liquid comprises determining a mass of dispensed liquid.

[0030] It should be noted that any embodiment of the method according to the first aspect as described above may be combined with one or more further embodiments of the method according to the first aspect as described above, which may make it possible to provide particularly advantageous synergistic effects.

[0031] According to a second aspect of the present disclosure, there is provided a computer program element that, when executed on a computing device of a system for evaluating a fluid substance, instructs the computing device and / or system to perform steps of a method according to the first aspect and / or according to any embodiment of the first aspect.

[0032] According to a third aspect of the present disclosure, there is provided a non-transitory computer readable medium having stored thereon a computer program element according to the second aspect of the present disclosure.

[0033] According to a fourth aspect of the present disclosure, there is provided a system for evaluating a fluidic substance. In particular, the system according to the fourth aspect may refer to a dispensing tip evaluation system, such as the one illustratively described with reference to FIG. 1, and / or a sample quality detection device, such as the one illustratively described with reference to FIGS. 42-55. The system according to the fourth aspect may also refer to a volume detection system, such as the one illustratively described with reference to FIGS. 1, 6-15, and / or 9-21. The system according to the fourth aspect may also refer to a correlation data generation system, such as the one illustratively described with reference to FIGS. 8-21.

[0034] A system according to a fourth aspect includes a sample pipetting device having a dispensing tip. The sample pipetting device may refer to a substance pipetting device. In that, the sample pipetting device is configured to at least partially engage the dispensing tip and aspirate a fluidic substance into the dispensing tip. The system further includes an image capture unit and at least one computing device, which may include and / or refer to a processing device. In that, the image capture unit is configured to capture an image of at least a portion of the fluidic 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 fluidic substance contained in the dispensing tip based on the multiple color parameters, the sample classification result representing and / or indicative of the concentration of at least one interfering substance in the fluidic substance.

[0035] In other words, the system may include a sample pipetting device having a dispensing tip, the sample pipetting device configured to engage the dispensing tip, and the sample pipetting device configured to aspirate a fluidic material into the dispensing tip. The system may further include an image capture unit configured to capture an image of at least a portion of the fluidic 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 use the image capture unit to capture an image of at least a portion of the fluidic material in the dispensing tip, obtain a plurality of color parameters of at least a portion of the image, and generate a sample classification result for the fluidic material contained in the dispensing tip based on the plurality of color parameters, wherein the sample classification result represents a concentration of at least one interferent in the fluidic material.

[0036] According to an embodiment of the system of the fourth aspect, the computing device further comprises: generating a histogram of at least a portion of an image, said histogram comprising a plurality of color channels; obtaining a plurality of average values for a plurality of color channels; and / or obtaining multiple Riemann sums of multiple color channels; configured to: and / or software instructions further cause the system to do so. Therein, the plurality of color parameters includes a plurality of means and / or a plurality of Riemann sums of color channels.

[0037] According to an embodiment of the system of the fourth aspect, the sample classification result comprises at least one classification identifier, the at least one classification identifier correlated with at least a portion of the plurality of color parameters and / or correlated with the concentration of at least one interferent in the fluidic material, wherein the sample classification result may include at least one of the plurality of classification identifiers, the plurality of classification identifiers correlated with the plurality of color parameters.

[0038] According to an embodiment of the system of the fourth aspect, the computing device further comprises: Identifying a reference point in the image, said reference point being associated with a dispensing tip; identifying a surface level of the fluidic material within the dispensing tip in the image; Determining and / or measuring the distance between a reference point and a surface level; converting the distance to a volume of the fluid material based on correlation data, the correlation data including information about the correlation between the volume within the dispensing tip and the distance from a reference point to multiple surface levels within the dispensing tip; The software instructions further cause the system to perform the following: Therein, correlation data may also refer to an equation and / or a functional relationship between distance and volume.

[0039] According to an embodiment of the system of 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, wherein the reference point in the image may include the reference line formed on the body of the dispensing tip.

[0040] According to an 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 segmentation of the captured image.

[0041] According to a system embodiment of the fourth aspect, the computing device is configured to search for and / or identify a pattern representing a reference line within the captured image.

[0042] According to an 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.

[0043] According to a system embodiment of the fourth aspect, the computing device is configured to determine a match rate, a match score, and / or a correlation value of the portion of the captured image and the reference image.

[0044] According to an 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 fluidic material from a side of the dispensing tip.

[0045] According to an embodiment of the system of the fourth aspect, the system further comprises a sample pipetting module, the image capture unit being attached to the sample pipetting module.

[0046] According to an embodiment of the system of the fourth aspect, the system further comprises a light source positioned opposite the image capture unit and positioned on a side of the dispensing tip, the light source being configured to illuminate the dispensing tip from the side of the dispensing tip.

[0047] According to an embodiment of the system of the fourth aspect, the system further comprises a light source and a sample pipetting module, wherein the light source and the image capturing unit are attached to the sample pipetting module and / or configured to move, for example horizontally, together with the sample pipetting module so that an image of the dispensing tip can be captured at any position of the sample pipetting module. Specifically, the image may be captured at any position along the trajectory and / or along the sample transport guide of the sample pipetting module.

[0048] According to an embodiment of the system of the fourth aspect, the sample pipetting device is configured to aspirate liquid into the further dispensing tip, the system is configured to determine a volume of the aspirated liquid, the image capture unit is configured to capture a further image of the further dispensing tip, and the computing device is configured to determine a pixel distance between reference points in the image associated with the further dispensing tip and to correlate the determined volume with the determined pixel distance.

[0049] According to an embodiment of the system of the fourth aspect, the computing device is configured to generate correlation data based on the determined volume and the determined pixel distance.

[0050] According to an embodiment of the system of the fourth aspect, the correlation data is generated based on multiple correlations between multiple determined pixel distances and multiple determined volumes of liquid aspirated into the further dispensing tip.

[0051] According to an embodiment of the system of the fourth aspect, the aspirated liquid comprises a dye solution. Alternatively, or in addition, the system is configured to determine the volume of the aspirated liquid based on spectrophotometry.

[0052] According to an embodiment of the system of the fourth aspect, the system is configured to determine a mass of the aspirated liquid and to determine a volume of the aspirated liquid based on the determined mass of the aspirated liquid.

[0053] It should be noted that any embodiment of the system according to the fourth aspect as described above may be combined with one or more further embodiments of the system according to the fourth aspect as described above, which may make it possible to provide particularly advantageous synergistic effects.

[0054] 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 also be a feature, function, characteristic, step, and / or element of the method according to the first aspect as described above and below, and vice versa.

[0055] According to a fifth aspect of the present disclosure, there is provided a system for evaluating a fluidic substance. Among other things, the system according to the fifth aspect may refer to a tip alignment detection device, for example, as illustratively described with reference to Figures 56-58. The system according to the fifth aspect may further refer to a dispensing tip evaluation system and / or a volume detection system, for example, as illustratively described with reference to Figures 1, 5-15, and / or 9-21. The system according to the fifth aspect may also refer to a correlation data generation system, for example, as illustratively described with reference to Figures 8-21.

[0056] A system according to a fifth aspect includes a sample pipetting device configured to at least partially engage a dispensing tip, the sample pipetting device configured to aspirate a fluidic substance into the dispensing tip, the dispensing tip having at least one reference line. The sample pipetting device may refer to the substance pipetting device. The system further comprises: an image capture unit configured to capture an image of at least a portion of the dispensing tip; At least one computing device, wherein the at least one computing device may include a processing device, the processing device comprising: identifying at least one reference line of the dispensing tip from a portion of the image of the dispensing tip; determining at least one characteristic of the at least one reference line; comparing at least one characteristic of the at least one reference line to a threshold; wherein the threshold represents a misalignment of the dispensing tip; and The computing device may be configured to determine whether a characteristic of the at least one reference line satisfies a threshold value, the threshold value representing misalignment of the dispensing tip, wherein the misalignment may refer to misalignment with respect to the image capture unit and / or with respect to the sample pipetting module.

[0057] 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 computing device, cause the system to: identifying at least one reference line of the dispensing tip from the image of the dispensing tip; obtaining one or more characteristics of at least one reference line; determining whether a characteristic of at least one reference line satisfies a threshold value, the threshold value being indicative of misalignment of the dispensing tip; Have them do this.

[0058] According to an embodiment of the system of the fifth aspect, the at least one reference line comprises a first reference line and a second reference line formed on the dispensing tip.

[0059] According to an embodiment of the system of the fifth aspect, 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 further comprises: determining and / or calculating a length of a first reference line; Determining and / or calculating the length of the second reference line; determining and / or calculating an angle of a line relative to at least one of the first reference line and the second reference line, the line connecting a pre-determined point on the first reference line and a pre-determined point on the second reference line; obtaining at least one characteristic of the at least one reference line based on determining misalignment of the dispensing tip, e.g., with respect to the image capture unit and / or with respect to the sample pipetting module, 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; The software instructions further cause the system to perform the following:

[0060] According to system embodiments of the fifth aspect, the system is configured to, and / or the software instructions further cause the system to, prevent the sample pipetting device from aspirating fluidic material into the dispensing tip in response to determining a mismatch. By way of example, the computing device may be configured to generate and / or output an interrupt signal in response to determining a mismatch.

[0061] According to an embodiment of the system of the fifth aspect, the at least one computing device is further configured to flag and / or initiate aspiration of fluidic material into the dispensing tip in response to determining the mismatch, and / or the software instructions further cause the system to do so.

[0062] According to an embodiment of the system of the fifth aspect, the at least one computing device further comprises: identifying at least one reference line of the dispensing tip from a portion of the image of the dispensing tip; identifying a surface level of the fluidic material within the dispensing tip in the image; determining and / or measuring a distance between at least one reference line and a surface level; determining a volume of the fluid material by converting the distance to a volume of the fluid material based on correlation data, the correlation data including information about the correlation between the volume within the dispensing tip and the distance from at least one reference line to a plurality of surface levels within the dispensing tip; The software instructions further cause the system to perform the following: Therein, correlation data may also refer to an equation and / or a functional relationship between distance and volume.

[0063] According to an embodiment of the system of the fifth aspect, the computing device is configured to determine the reference line based on pattern matching and / or based on segmentation of the captured image.

[0064] According to an embodiment of the system of the fifth aspect, the computing device is configured to search for a pattern representing a reference line within the captured image.

[0065] According to an 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.

[0066] According to an embodiment of the system of the fifth aspect, the computing device is configured to determine a match rate, a match score, and / or a correlation value of the portion of the captured image and the reference image.

[0067] According to an embodiment of the system of the fifth aspect, 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 further comprises: determining and / or calculating a length of a first reference line in the image; determining and / or calculating a length of a second reference line in the image; determining and / or calculating an angle of a line relative to at least one of a first reference line and a second reference line, said line connecting a pre-determined point on the first reference line and a pre-determined point on the second reference line; determining misalignment of the dispensing tip, e.g., relative to the image capture unit and / or relative to the sample pipetting module, 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; adjusting the volume of the fluidic material based on the determination of the mismatch; The software instructions further cause the system to perform the following:

[0068] According to an embodiment of the system of the fifth aspect, the dispensing tip misalignment includes lateral misalignment and depth misalignment, wherein lateral misalignment may refer to displacement of the dispensing tip relative to the optical axis of the camera and / or image capture unit, and depth misalignment may refer to displacement of the dispensing tip along the optical axis of the camera and / or image capture unit.

[0069] According to an embodiment of the system of the fifth aspect, 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 further comprises: Identifying a predetermined point of a first reference line within the image; identifying a predetermined point of a second reference line within the image; defining a matching line connecting a predetermined point on the first reference line and a predetermined point on the second reference line; determining an angle of the alignment line relative to at least one of the first reference line and the second reference line; comparing the angle to a threshold angle value; wherein the threshold angle value represents lateral misalignment of the dispensing tip, and / or the software instructions further cause the system to do the same. Therein, it may be determined whether the angle of the alignment line is less than a threshold angle value, the threshold angle value representing a lateral misalignment of the dispensing tip.

[0070] According to an embodiment of the system of the fifth aspect, the pre-determined point of the first reference line is a center point of the first reference line in the image, and the pre-determined point of the second reference line is a center point of the second reference line in the image.

[0071] According to an 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 pipetting device from aspirating fluidic 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 an interrupt 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 a threshold angle value. Thus, the system may be configured to prevent the material pipetting device and / or the sample pipetting device from aspirating fluidic material into the dispensing tip in response to determining that the angle of the alignment line is at least the threshold angle value.

[0072] According to an embodiment of the system of the fifth aspect, the at least one computing device is further configured to, and / or software instructions further cause the system to, flag aspiration of fluidic material into the dispensing tip and / or initiate aspiration of fluidic material into the dispensing tip, e.g., by flagging the aspiration, 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. Thus, the system may be configured to flag aspiration of fluidic material into the dispensing tip in response to determining that the angle of the alignment line is at least the threshold angle value.

[0073] According to an embodiment of the system of the fifth aspect, the at least one computing device further comprises: determining and / or identifying a length of at least one reference line based on the captured image of the tip; obtaining an actual length of at least one reference line; calculating a ratio between a length of the at least one reference line and an actual length of the at least one reference line; determining a depth mismatch of the dispensing tip based on the ratio; The software instructions further cause the system to perform the following:

[0074] Alternatively, or in addition, the software instructions may further cause the system to: identifying a length of a first reference line from the captured image of the tip; obtaining an actual length of the first reference line; calculating a ratio between the length of the first reference line and the actual length of the first reference line; determining a depth mismatch of the dispensing tip based on the ratio; Have them do this.

[0075] According to an embodiment of the system of the fifth aspect, the system is further configured to, and / or the software instructions further cause the system to, adjust the determined volume of the fluidic substance based on the ratio.

[0076] According to an embodiment of the system of the fifth aspect, the system further comprises a light source and a sample pipetting module, wherein the light source and the image capturing unit are attached to the sample pipetting module and / or configured to move, e.g., horizontally, together with the sample pipetting module so that an image of the dispensing tip can be captured at any position of the sample pipetting module. By way of example, the image may be captured at any position along a trajectory and / or along a sample transport guide of the sample pipetting module.

[0077] According to an embodiment of the system of the fifth aspect, the sample pipetting device is configured to aspirate liquid into the further dispensing tip, and the system is configured to determine a volume of the aspirated liquid, the image capture unit is configured to capture a further image of the further dispensing tip, and the computing device is configured to determine a pixel distance between reference points in the image associated with the further dispensing tip, and to correlate the determined volume with the determined pixel distance.

[0078] According to an embodiment of the system of the fifth aspect, the computing device is configured to generate correlation data based on the determined volume and the determined pixel distance.

[0079] According to an embodiment of the system of the fifth aspect, the correlation data is generated based on multiple correlations between multiple determined pixel distances and multiple determined volumes of liquid aspirated into the further dispensing tip.

[0080] According to an embodiment of the system of the fifth aspect, the aspirated liquid comprises a dye solution, and / or the system is configured to determine the volume of the aspirated liquid based on spectrophotometry.

[0081] According to an embodiment of the system of the fifth aspect, the system is configured to determine a mass of the aspirated liquid and to determine a volume of the aspirated liquid based on the determined mass of the aspirated liquid.

[0082] It should be noted that any embodiment of the system according to the fifth aspect as described above may be combined with one or more further embodiments of the system according to the fifth aspect as described above, which may make it possible to provide particularly advantageous synergistic effects.

[0083] According to a sixth aspect of the present disclosure, there is provided a method of evaluating a fluidic substance in a container. Among other things, the method according to the sixth aspect may refer to a method for operating a tip alignment detection device, a dispensing tip integrity assessment device, a volume detection system, and / or a dispensing tip assessment system, for example, as illustratively described with reference to Figures 1, 5-15, 9-21, and / or 56-68.

[0084] The method according to the sixth aspect comprises: capturing an image of at least a portion of a container using an image capture device, the container may be a dispensing tip; using at least one computing device to determine and / or identify a first reference line and a second reference line of the container from an image of the container; determining and / or obtaining at least one characteristic of at least one of the first reference line and the second reference line; Includes. In one embodiment, the at least one characteristic comprises at least one of a length of the first reference line, a length of the second reference line, and an angle of a line relative to at least one of the first reference line and the second reference line, the line connecting a predetermined point on the first reference line and a predetermined point on the second reference line. The method according to the sixth aspect further includes comparing the at least one characteristic of at least one of the first reference line and the second reference line to a threshold value indicative of misalignment of the dispensing tip.

[0085] In other words, the method according to the sixth aspect: capturing an image of at least a portion of the container using an image capture unit; identifying, using at least one computing device, a first reference line and a second reference line of the dispensing tip from an image of the dispensing tip; obtaining one or more characteristics of the first and second reference lines, the characteristics including at least one of a length of the first reference line, a length of the second reference line, and an angle of a line relative to the reference lines, the line connecting a predetermined point on the first reference line and a predetermined point on the second reference line; determining whether a characteristic of at least one reference line satisfies a threshold value, the threshold value representing misalignment of the dispensing tip; may include:

[0086] According to an 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 segmentation of the captured image.

[0087] According to an embodiment of the method of the sixth aspect, determining the first reference line and the second reference line comprises searching for a pattern representing the first reference line and / or the second reference line in the captured image.

[0088] According to an embodiment of the method of the sixth aspect, determining the first and second reference lines comprises comparing at least a portion of the captured image to a reference image.

[0089] According to an embodiment of the method of the sixth aspect, the method further comprises determining a match rate, a match score, and / or a correlation value of the portion of the captured image and the reference image.

[0090] According to an embodiment of the method of the sixth aspect, the container contains a fluidic substance and the method further comprises: identifying a surface level of the fluid material within the container in the captured image; determining a distance between at least one of the first and second reference lines and a surface level; determining a volume of the fluid material by converting the distance to a volume of the fluid material based on correlation data, the correlation data including information about a correlation between a volume within the container and a distance from at least one of the first reference line and the second reference line to a plurality of surface levels within the container; Includes. Therein, correlation data may also refer to an equation and / or a functional relationship between distance and volume.

[0091] According to an embodiment of the method of the sixth aspect, the method further comprises: determining a length of a first reference line in the image; determining a length of a second reference line in the image; determining an angle of a line relative to at least one of the first reference line and the second reference line, the line connecting a predetermined point on the first reference line and a predetermined point on the second reference line; determining a misalignment of the container based on at least one of a length of the first reference line, a length of the second reference line, and an angle of the line; adjusting the volume of the fluidic material based on the determination of the mismatch; Includes. Therein, misalignment may refer to misalignment with respect to the image capture unit and / or with respect to the sample pipetting module.

[0092] According to an embodiment of the method of the sixth aspect, the container misalignment includes lateral misalignment and depth misalignment, wherein lateral misalignment may refer to displacement of the dispensing tip relative to the optical axis of the camera and / or image capture unit, and depth misalignment may refer to displacement of the dispensing tip along the optical axis of the camera and / or image capture unit.

[0093] According to an embodiment of the method of the sixth aspect, the method further comprises: Identifying a predetermined point of a first reference line within the image; identifying a predetermined point of a second reference line within the image; defining a matching line connecting a predetermined point on the first reference line and a predetermined point on the second reference line; determining an angle of the alignment line relative to at least one of the first reference line and the second reference line; comparing the angle to a threshold angle value, the threshold angle value representing lateral misalignment of the container; Includes.

[0094] According to an embodiment of the method of the sixth aspect, the pre-determined point of the first reference line is a center point of the first reference line in the image, and the pre-determined point of the second reference line is a center point of the second reference line in the image.

[0095] According to an embodiment of the method of the sixth aspect, the method further includes preventing aspiration of the fluidic material into the container in response to determining that an 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, an interrupt signal preventing aspiration may be generated in response to determining that an 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.

[0096] According to an embodiment of the method of the sixth aspect, the method further includes a step of flagging the suction of fluid material into the container and / or a step of initiating the suction 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 meets and / or exceeds a threshold angle value.

[0097] According to an embodiment of the method of the sixth aspect, the method further comprises: determining a length of at least one of the first reference line and the second reference line based on the captured image of the container; obtaining, for example, from a data storage device, an actual length of at least one of the first reference line and the second reference line; calculating a ratio between a length of at least one of the first and second reference lines and an actual length of at least one of the first and second reference lines; determining a depth mismatch of the container based on the ratio; Includes.

[0098] According to an embodiment of the method of the sixth aspect, the method further comprises adjusting the determined volume of the fluidic material based on the ratio.

[0099] It should be noted that any embodiment of the method according to the sixth aspect as described above may be combined with one or more further embodiments of the method according to the sixth aspect as described above, which may make it possible to provide particularly advantageous synergistic effects.

[0100] 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 also be a feature, function, characteristic, step, and / or element of the method according to the sixth aspect as described above and below, and vice versa.

[0101] According to a seventh aspect of the present disclosure there is provided a computer program element which, when executed on a computing device of a system for evaluating a fluid substance, instructs the computing device and / or system to perform steps of the method according to the sixth aspect.

[0102] According to an eighth aspect of the present disclosure, there is provided a non-transitory computer readable medium having stored thereon a computer program element according to the seventh aspect.

[0103] According to a ninth aspect of the present disclosure, there is provided a system for evaluating a fluid substance. The system according to the ninth aspect may refer to, for example, a particle concentration check system as illustratively described with reference to Figures 69-79, a volume detection system as illustratively described with reference to Figures 5-15, a correlation data generation system as illustratively described with reference to Figures 8-21, and / or a reaction vessel residual volume detection device as illustratively described with reference to Figures 32-34.

[0104] A system according to a ninth aspect comprises a container carriage device configured to support and / or hold one or more containers, a sample pipetting device and / or a substance pipetting device configured to dispense fluidic substances into at least one of the containers on the container carriage device, an image capture device configured to capture an image of at least one of the containers on the container carriage device, and at least one processing device and / or at least one computing device. Among them, this system is Dispensing at least one fluidic substance into a container using a sample pipetting device; capturing an image of a container on a container carriage device using an image capture device; analyzing the image of the container using at least one processing device to determine a volume of the at least one fluidic substance dispensed in the container; analyzing the images of the container using at least one processing device to determine a particle concentration of the entire volume of the fluid material in the container; The device is configured to:

[0105] 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: Dispensing one or more fluidic substances into a container; acquiring an image of a container on a container carriage device; analyzing the image of the container to determine a volume of the dispensed fluidic material in the container; analyzing the image of the container to determine a particle concentration for the entire volume of the fluid material in the container; Have them do this.

[0106] According to an embodiment of the system of the ninth aspect, the total volume of fluidic material comprises at least one bodily fluid and / or at least one reagent.

[0107] According to an embodiment of the system of the ninth aspect, the system further comprises: capturing and / or obtaining a first image of the container using an image capture device after dispensing a reagent into at least one fluidic substance contained within the container, wherein the at least one fluidic substance comprises at least one bodily fluid; capturing and / or obtaining a second image of the container using the image capture device after mixing the added reagent with the at least one fluidic substance in the container; analyzing a first image of the container using at least one processing device to determine a volume of dispensed reagent in the container; analyzing, using at least one processing device, a second image of the container to determine a particle concentration of the entire volume of the fluidic material in the container; The software instructions further cause the system to perform the following:

[0108] According to an embodiment of the system of the ninth aspect, the particle concentration comprises a concentration of paramagnetic particles.

[0109] According to an embodiment of the system of the ninth aspect, the at least one reagent comprises a chemiluminescent substrate.

[0110] According to an 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 approximately 6.5 seconds after mixing.

[0111] According to an embodiment of the system of the ninth aspect, the image capture device is mounted to the container carriage device, the image capture device configured and / or arranged to capture an image of the container from a side of the container.

[0112] According to an embodiment of the system of the ninth aspect, the system further comprises a light source, the light source and the image capture device being mounted to the container carriage device such that the light source is positioned opposite the image capture device.

[0113] According to an embodiment of the system of the ninth aspect, the container carriage device is a cleaning wheel comprising a rotatable plate, the rotatable plate configured to rotate the container to the image capture device.

[0114] According to an embodiment of the system of the ninth aspect, the system is further configured to detect whether a container is present on the container carriage device, for example by suitable hardware and / or software means, and / or software instructions further cause the system to do so.

[0115] According to an embodiment of the system of the ninth aspect, at least one processing device comprises: determining and / or identifying reference points within the image, the reference points being associated with the container; determining and / or identifying a surface level of at least one fluid substance within the container in the image; Determining and / or measuring the distance between a reference point and a surface level; converting the distance to a volume of the at least one fluidic substance and / or reagent dispensed based on correlation data, the correlation data including information about the correlation between the volume within the container and the distance from a reference point to a plurality of surface levels within the container; The software instructions further cause the system to perform the following:

[0116] According to an embodiment of the system of the ninth aspect, determining and / or identifying the reference point comprises determining and / or identifying a bottom portion of the container.

[0117] According to an embodiment of the system of the ninth aspect, the distance is measured by pixel distance.

[0118] According to an embodiment of the system of the ninth aspect, the processing device is configured to determine the reference points based on pattern matching and / or based on segmentation of the captured image.

[0119] According to an embodiment of the system of the ninth aspect, the processing device is configured to search for a pattern representing the reference point within the captured image.

[0120] According to an 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.

[0121] According to an embodiment of the system of the ninth aspect, the processing device is configured to determine a match rate, a match score, and / or a correlation value of the portion of the captured image and the reference image.

[0122] According to an embodiment of the system of the ninth aspect, the sample pipetting device is configured to aspirate liquid into a further container, the system is configured to determine a volume of the aspirated liquid, the image capture unit is configured to capture a further image of the further container, and the processing device is configured to determine a pixel distance between reference points in the image associated with the further container, and to correlate the determined volume with the determined pixel distance.

[0123] According to an 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.

[0124] According to an embodiment of the system of the ninth aspect, the correlation data is generated based on a plurality of correlations between a plurality of determined pixel distances and a plurality of determined volumes of liquid aspirated into the further container.

[0125] According to an embodiment of the system of the ninth aspect, the aspirated liquid comprises a dye solution. Alternatively, or in addition, the system is configured to determine the volume of the aspirated liquid based on spectrophotometry.

[0126] According to an embodiment of the system of the ninth aspect, the system is configured to determine a mass of the aspirated liquid and to determine a volume of the aspirated liquid based on the determined mass of the aspirated liquid.

[0127] According to an embodiment of the system of the ninth aspect, the at least one processing device further comprises: obtaining and / or determining the brightness of the total volume of the fluid material from the image of the container, e.g., based on receiving brightness values from a sensor and / or e.g., based on image processing; determining a particle concentration for the entire volume of the fluid material based on the brightness of the fluid material and the calibration data; comparing the determined particle concentration to a threshold; flagging a container containing the entire volume of the fluid material in response to determining that the determined particle concentration is below a threshold; The software instructions further cause the system to perform the following:

[0128] According to an embodiment of the system of the ninth aspect, the system further comprises: aspirating at least a portion of the fluidic material from the container using a sample pipetting device; capturing a third image of at least a portion of the container using an image capture device; comparing the third image with a reference image using at least one processing device; using at least one processing device to determine a match score based on the similarity between the third image and the reference image; comparing the generated match score to a threshold; The software instructions further cause the system to perform the following:

[0129] According to an embodiment of the system of the ninth aspect, the system is further configured to determine, using at least one processing device, an area of interest in the third image, and / or the software instructions further cause the system to do so, and wherein comparing the third image comprises comparing the area of interest in the third image with at least a portion of the reference image.

[0130] According to an embodiment of the system of the ninth aspect, the area of interest comprises a region adjacent the bottom of the container.

[0131] According to an embodiment of the system of the ninth aspect, the system further comprises: flagging the result of aspiration from the container when the match score is equal to and / or below a threshold value; and / or Flagging aspiration results from a container when the match score does not exceed a threshold The software instructions further cause the system to perform the following:

[0132] According to an embodiment of the system of the ninth aspect, the container carriage device comprises a plurality of container slots, each container slot configured to support a container, and the system further comprises: capturing a fourth image of one of the plurality of container slots at a first position of the container carriage device using the image capture device; comparing the fourth image with a reference image using at least one processing device; generating, using at least one processing device, a match score based on the similarity between the fourth image and the reference image; comparing the match score to a threshold; The software instructions further cause the system to perform the following:

[0133] According to an embodiment of the system of the ninth aspect, a match score exceeding and / or meeting a threshold value indicates the absence of a container in one of the plurality of container slots.

[0134] According to an embodiment of the system of the ninth aspect, the system is configured to remove a container from one of the plurality of container slots when the match score is below a threshold, and / or the software instructions further cause the system to remove a container from one of the plurality of container slots when the match score does not meet a threshold.

[0135] According to an embodiment of the system of the ninth aspect, the system is configured to move the container carriage device to a second position after and / or in response to determining that the match score exceeds and / or meets a threshold. Alternatively, or in addition, the software instructions further cause the system to move the container carriage device to the second position after determining that the match score exceeds the threshold.

[0136] It should be noted that any embodiment of the system according to the ninth aspect as described above may be combined with one or more further embodiments of the system according to the ninth aspect as described above, which may make it possible to provide particularly advantageous synergistic effects.

[0137] According to a tenth aspect of the present disclosure, there is provided a method for evaluating a fluid substance in a container. The method according to the tenth aspect may refer to, for example, a method for operating a particle concentration check system such as those illustratively described with reference to Figures 69-79 and / or a method for operating a volume detection system such as those illustratively described with reference to Figures 5-15.

[0138] The method according to the tenth aspect comprises: Dispensing at least one fluidic substance into a container using a sample pipetting device; using an image capture device to capture and / or obtain an image of at least a portion of a container arranged on a container carriage device, the container carriage device being configured to support and / or hold one or more containers; analyzing, using at least one computing device, the image of the container to determine a volume of the at least one dispensed fluidic substance in the container; analyzing the images of the container using at least one computing device to determine a particle concentration of the entire volume of the fluid material in the container; Includes. Therein, the term "total volume of fluidic material" may refer to at least one dispensed fluidic material, and optionally at least one added reagent.

[0139] According to an embodiment of the method of the tenth aspect, the step of capturing and / or obtaining an image of the container comprises: capturing and / or obtaining a first image of the container using an image capture device after dispensing a reagent into at least one fluidic substance contained within the container, wherein the at least one fluidic substance includes at least one bodily fluid; capturing and / or obtaining a second image of the container using the image capture device, e.g., after adding the reagent and / or mixing the added reagent with at least one fluidic substance in the container; Includes. In which, analyzing the image of the container and determining the volume of at least one dispensed fluidic substance includes analyzing a first image of the container and determining the volume of a dispensed reagent contained in the container, and analyzing the image of the container and determining the particle concentration of the total volume of the fluidic substance includes analyzing a second image of the container and determining the particle concentration of the total volume of the fluidic substance in the container.

[0140] It should be noted that any embodiment of the method according to the tenth aspect as described above may be combined with one or more further embodiments of the method according to the tenth aspect as described above, which may make it possible to provide particularly advantageous synergistic effects.

[0141] 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 also be a feature, function, characteristic, step, and / or element of the method according to the tenth aspect as described above and below, and vice versa.

[0142] According to an eleventh aspect of the present disclosure, there is provided a computer program element that, when executed on a computing device of a system for evaluating a fluid substance, instructs the computing device and / or system to perform steps of the method according to the tenth aspect.

[0143] According to a twelfth aspect of the present disclosure, there is provided a non-transitory computer readable medium having stored thereon a computer program element according to the eleventh aspect.

[0144] According to a thirteenth aspect of the present disclosure, there is provided a method for evaluating a fluidic substance in a container. The method according to the thirteenth aspect may refer to, for example, a method for operating a volume detection system as illustratively described with reference to Figures 5-15, a method for operating a dispensing adjustment system as illustratively described with reference to Figures 35-36, a method for operating a correlation data generation system as illustratively described with reference to Figures 8-21, and / or a method for operating a residual volume detection device as illustratively described with reference to Figures 32-34.

[0145] The method according to the thirteenth aspect comprises: Dispensing a fluidic substance into a container using a substance dispensing device; determining and / or measuring a volume of the fluidic material in the container using at least one computing device; receiving operational information of a fluidic material dispensing device, the operational information including operational parameters of the fluidic material dispensing device; receiving a target dispense volume of a fluidic material; comparing the determined volume of the fluidic material to a target dispense volume; generating calibration information for the substance dispensing device; adjusting operating parameters of the substance dispensing device based on the calibration information; Includes.

[0146] According to an embodiment of the method of the thirteenth aspect, the step of determining and / or measuring the volume of the fluidic substance comprises: capturing an image of at least a portion of the container using an image capture device; using at least one computing device to identify reference points in the image, the reference points being associated with containers; identifying a surface level of a fluid material within the container in the image using at least one computing device; determining the distance between a reference point and a surface level; converting the distance to a volume of the fluid material based on correlation data, the correlation data including information about the correlation between the volume within the container and the distance from a reference point to a plurality of surface levels within the container; Includes.

[0147] According to an embodiment of the method of the thirteenth aspect, the method further comprises: providing the liquid to a further container; determining the volume of liquid dispensed; capturing a further image of the container; determining pixel distances between reference points in the image associated with the further container; correlating the determined volume with the determined pixel distance; Includes.

[0148] According to an embodiment of the method of the thirteenth aspect, the method further comprises generating correlation data based on the determined volume and the determined pixel distance.

[0149] According to an embodiment of the method of the thirteenth aspect, the correlation data is generated based on a plurality of correlations between a plurality of determined pixel distances and a plurality of determined volumes of liquid to be dispensed into the further container.

[0150] According to an embodiment of the method of the thirteenth aspect, the dispensed liquid comprises a dye solution. Alternatively or additionally, the volume of the dispensed liquid is determined spectrophotometrically.

[0151] According to an embodiment of the method of the thirteenth aspect, determining the volume of dispensed liquid comprises determining a mass of dispensed liquid.

[0152] According to an embodiment of the method of the thirteenth aspect, the method further comprises: aspirating at least a portion of the fluidic material from the container; capturing an image of at least a portion of the container using an image capture device; comparing the image with a reference image; generating a match score based on the similarity between the image and a reference image; Includes.

[0153] According to an embodiment of the method of the thirteenth aspect, the method further comprises: comparing the match score to a threshold; and / or Determining that the match score exceeds a threshold. Includes.

[0154] According to an embodiment of the method of the thirteenth aspect, the method further comprises determining an area of interest in the image, and wherein comparing the images comprises comparing the area of interest in the image with at least a portion of the reference image.

[0155] According to an embodiment of the method of the thirteenth aspect, the area of interest comprises a region adjacent the bottom of the container.

[0156] According to an embodiment of the method of the thirteenth aspect, the method further comprises flagging the result of aspiration from the container when the match score meets and / or falls below a threshold.

[0157] According to an embodiment of the method of the thirteenth aspect, the method further comprises: arranging a plurality of containers within a plurality of container slots of a container carriage device; capturing an image of one of the plurality of container slots at a first position of the container carriage device using an image capture device; comparing the image with a reference image; generating a match score based on the similarity between the image and a reference image; Includes.

[0158] According to an embodiment of the method of the thirteenth aspect, the method further comprises: comparing the match score to a threshold; and / or determining whether the match score exceeds and / or meets a threshold, wherein a match score exceeding the threshold indicates the absence of a container in one of the plurality of container slots; Includes.

[0159] According to an embodiment of the method of the thirteenth aspect, the method further comprises removing the container from one of the plurality of container slots when the match score is below a threshold.

[0160] According to an embodiment of the method of the thirteenth aspect, the method further includes moving the container carriage device to a second position after determining that the match score exceeds and / or meets the threshold.

[0161] It should be noted that any embodiment of the method according to the thirteenth aspect as described above may be combined with one or more further embodiments of the method according to the thirteenth aspect as described above, which may make it possible to provide particularly advantageous synergistic effects.

[0162] 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 also be a feature, function, characteristic, step, and / or element of the method according to the thirteenth aspect as described above and below, and vice versa.

[0163] According to a fourteenth aspect of the present disclosure, there is provided a computer program element which, when executed on a computing device of a system for evaluating a fluid substance, instructs the computing device and / or system to perform steps of the method according to the thirteenth aspect.

[0164] According to a fifteenth aspect of the present disclosure, there is provided a non-transitory computer readable medium having stored thereon a computer program element according to the fourteenth aspect. The present invention provides, for example, the following. (Item 1) 1. A method for evaluating a fluid substance in a container, comprising: capturing an image of at least a portion of the container using an image capture device; obtaining, using at least one computing device, a plurality of color parameters of at least a portion of the image; generating a sample classification of the fluidic material contained in the container based on the plurality of color parameters; Including, The method, wherein the sample classification result represents a concentration of at least one interferent in the fluid material. (Item 2) The step of obtaining a plurality of color parameters includes: generating a histogram of at least a portion of the image, the histogram comprising a plurality of color channels; obtaining a plurality of average values of the plurality of color channels, the plurality of color parameters comprising the plurality of average values of the plurality of color channels; Item 1. The method according to item 1, comprising: (Item 3) The step of obtaining a plurality of color parameters includes: generating a histogram of at least a portion of the image, the histogram comprising a plurality of color channels; obtaining a plurality of Riemann sums of the plurality of color channels; Including, 3. The method of any of items 1 and 2, wherein the plurality of color parameters includes the plurality of Riemann sums of the plurality of color channels. (Item 4) The step of obtaining a plurality of color parameters includes: generating a histogram of at least a portion of the image, the histogram comprising a plurality of color channels; obtaining a plurality of modes for the plurality of color channels; and / or obtaining a plurality of maxima of the plurality of color channels; and / or obtaining a plurality of minimum values of the plurality of color channels, wherein the plurality of color parameters include the plurality of modes, maximum values, and / or minimum values of the plurality of color channels; 3. The method according to any of the preceding items, comprising: (Item 5) The step of obtaining a plurality of color parameters includes: generating a histogram of at least a portion of the image, the histogram comprising a plurality of color channels; obtaining a plurality of histogram heads for the plurality of color channels; and / or obtaining a plurality of histogram tails for the plurality of color channels; obtaining a plurality of histogram head ratios for the plurality of color channels; and / or obtaining a plurality of histogram tail ratios for the plurality of color channels, wherein the plurality of color parameters include the plurality of histogram heads, histogram tails, histogram head ratios, and / or histogram tail ratios for the plurality of color channels; 3. The method according to any of the preceding items, comprising: (Item 6) 5. The method of claim 1, wherein the plurality of color parameters includes at least one of a plurality of means of the color channels, a plurality of Riemann sums of the color channels, a plurality of modes of the color channels, a plurality of maxima of the color channels, a plurality of minima of the color channels, a plurality of histogram heads of the color channels, a plurality of histogram tails of the color channels, a plurality of histogram head ratios of the color channels, a plurality of histogram tail ratios of the color channels, or any combination of the foregoing. (Item 7) 7. The method according to any one of items 2-6, wherein the plurality of color channels includes a red component, a green component, and a blue component. (Item 8) the sample classification result comprises at least one classification identifier; 10. The method of claim 9, wherein the at least one classification identifier is correlated with at least a portion of the plurality of color parameters and / or is correlated with a concentration of the at least one interfering substance in the fluid material. (Item 9) 10. The method of claim 1, further comprising generating a flagging result based on the sample classification result, the flagging result indicating the quality of the fluid material. (Item 10) 10. The method of claim 1, wherein the at least one interfering substance is one or more selected from hemoglobin, icterus, and lipemia. (Item 11) 10. The method of claim 1, wherein the container is a dispensing tip configured to aspirate the fluidic material. (Item 12) 10. The method of claim 1, wherein the image capture device is configured and / or arranged to capture the image of the portion of the fluid material and / or the container from a side of the container. (Item 13) using the at least one computing device, identifying a reference point in the image, the reference point being associated with the container; using the at least one computing device to identify a surface level of the fluid material within the container in the image; determining the distance between the reference point and the surface level; converting the distance to a volume of the fluid material based on correlation data, the correlation data including information about a correlation between a volume within the container and distances from the reference point to a plurality of surface levels within the container; The method of any of the preceding items further comprising: (Item 14) Item 14. The method of item 13, wherein the distance is measured by pixel distance. (Item 15) the container is a dispensing tip configured to aspirate the fluidic material; 15. The method of any of items 13 or 14, wherein identifying a reference point comprises identifying a reference line formed on the dispensing tip. (Item 16) Item 16. The method of item 15, wherein the reference lines are identified based on pattern matching and / or segmentation of the captured image. (Item 17) 17. The method of any of items 15 or 16, wherein identifying the reference line comprises searching for a pattern in the captured image that represents the reference line. (Item 18) 18. The method of any of items 15-17, wherein identifying the reference line comprises comparing at least a portion of the captured image with a reference image. (Item 19) Item 19. The method of item 18, further comprising determining a match rate and / or a correlation value of the portion of the captured image and the reference image. (Item 20) providing the liquid to a further container; determining the volume of the dispensed liquid; capturing a further image of the container; determining pixel distances between reference points in the image associated with the further container; correlating the determined volume with the determined pixel distance; 3. The method of any preceding item, further comprising: (Item 21) 21. The method of claim 20, further comprising generating correlation data based on the determined volume and the determined pixel distance. (Item 22) Item 22. The method according to item 1, wherein the correlation data is generated based on a plurality of correlations between a plurality of determined pixel distances and a plurality of determined volumes of liquid to be dispensed into the further container. (Item 23) the dispensed liquid comprises a dye solution; and / or 23. The method of any of items 20-22, wherein the volume of the dispensed liquid is determined spectrophotometrically. (Item 24) 24. The method of any of items 20-23, wherein determining the volume of the dispensed liquid comprises determining a mass of the dispensed liquid. (Item 25) A computer program element that, when executed on a computing device of a system for evaluating a fluid substance, instructs said computing device to perform the steps of the method according to any of items 1-24. (Item 26) 26. A non-transitory computer-readable medium having stored thereon the computer program elements according to item 25. (Item 27) 1. A system for evaluating a fluid substance, comprising: a sample pipetting device having a dispensing tip, the sample pipetting device configured to at least partially engage the dispensing tip and to aspirate a fluidic material into the dispensing tip; an image capture unit; At least one computing device and Equipped with the image capture unit is configured to capture an image of at least a portion of the fluidic material in the dispensing tip; the computing device obtaining a plurality of color parameters of at least a portion of the image; generating a sample classification result for the fluidic material contained in the dispensing tip based on the plurality of color parameters; configured to: The sample classification result represents a concentration of at least one interferent in the fluid material. (Item 28) The computing device further comprises: generating a histogram of at least a portion of the image, the histogram comprising a plurality of color channels; obtaining a plurality of average values of the plurality of color channels; and / or obtaining multiple Riemann sums of the multiple color channels. configured to: Item 28. The system of item 27, wherein the plurality of color parameters includes the plurality of means and / or the plurality of Riemann sums of the plurality of color channels. (Item 29) the sample classification result comprises at least one classification identifier; 29. The system of any of items 27 and 28, wherein the at least one classification identifier is correlated with at least a portion of the plurality of color parameters and / or correlated with a concentration of the at least one interfering substance in the fluid material. (Item 30) The computing device further comprises: identifying a reference point within the image, the reference point being associated with the dispensing tip; identifying a surface level of the fluid material within the dispensing tip in the image; determining the distance between the reference point and the surface level; converting the distance to a volume of the fluid material based on correlation data, the correlation data including information about the correlation between a volume within the dispensing tip and distances from the reference point to multiple surface levels within the dispensing tip; 30. The system of any of items 27-29, configured to: (Item 31) 31. The system of any of items 27-30, wherein the computing device is configured to determine a reference line formed on the body of the dispensing tip, and to determine the reference point based on the determined reference line. (Item 32) Item 32. The system of item 31, wherein the computing device is configured to determine the reference line based on pattern matching and / or segmentation of the captured image. (Item 33) 33. The system of any of items 31 and 32, wherein the computing device is configured to search for a pattern representing the reference line in the captured image. (Item 34) 34. The system of any of items 31-33, wherein the computing device is configured to compare at least a portion of the captured image with a reference image. (Item 35) Item 36. The system of item 34, wherein the computing device is configured to determine a match rate and / or a correlation value of the portion of the captured image and the reference image. 36. The system of any of items 27-35, wherein the image capture unit is configured and / or arranged to capture the image of the portion of the fluidic material from a side of the dispensing tip. (Item 37) further comprising a sample pipetting module; 37. The system of any of items 27-36, wherein the image capture unit is attached to the sample pipetting module. (Item 38) further comprising a light source positioned opposite the image capture unit and positioned on a side of the dispensing tip; 38. The system of any of items 27-37, wherein the light source is configured to illuminate the dispensing tip from the side of the dispensing tip. (Item 39) a light source and a sample pipetting module; the light source and the image capture unit are attached to the sample pipetting module; and / or 39. The system of any of items 27-38, wherein the light source and the image capture unit are configured to move with the sample pipetting module so that an image of the dispensing tip can be captured at any position of the sample pipetting module. (Item 40) the sample pipetting device is configured to aspirate liquid into a further dispensing tip; the system is configured to determine a volume of the aspirated liquid; the image capture unit is configured to capture a further image of the further dispensing tip; 40. The system of any of items 27-39, wherein the computing device is configured to determine a pixel distance between reference points in the image associated with the further dispensing tip, and to correlate the determined volume with the determined pixel distance. (Item 41) Item 41. The system of item 40, wherein the computing device is configured to generate correlation data based on the determined volume and the determined pixel distance. (Item 42) The system of item 1 of item 41, wherein the correlation data is generated based on multiple correlations between multiple determined pixel distances and multiple determined volumes of liquid aspirated into the further dispensing tip. (Item 43) the aspirated liquid comprises a dye solution; and / or 43. The system of any of items 40-42, wherein the system is configured to determine the volume of the aspirated liquid based on spectrophotometry. (Item 44) 44. The system of any of items 40-43, wherein the system is configured to determine a mass of the aspirated liquid and to determine the volume of the aspirated liquid based on the determined mass of the aspirated liquid. (Item 45) 1. A system for evaluating a fluid substance, comprising: a sample pipetting device configured to at least partially engage a dispensing tip, the sample pipetting device configured to aspirate a fluidic 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, identifying the at least one reference line of the dispensing tip from the portion of the image of the dispensing tip; determining at least one characteristic of the at least one reference line; comparing the at least one characteristic of the at least one reference line to a threshold; wherein the threshold value represents a misalignment of the dispensing tip; and A system comprising: (Item 46) Item 46. The system of item 45, wherein the at least one reference line comprises a first reference line and a second reference line formed on the dispensing tip. (Item 47) 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 further comprises: obtaining the at least one characteristic of the at least one reference line, wherein obtaining the at least one characteristic includes: determining a length of the first reference line; determining a length of the second reference line; determining an angle of a line relative to at least one of the first reference line and the second reference line, the line connecting a predetermined point on the first reference line and a predetermined point on the second reference line; and a step based on determining the misalignment of the dispensing tip 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; 47. The system of any of items 45-46, configured to: (Item 48) 48. The system of any of items 45-47, wherein the system is configured to prevent the sample pipetting device from aspirating the fluidic material into the dispensing tip in response to determining the mismatch. (Item 49) The system of any of items 45-48, wherein the at least one computing device is further configured to flag and / or initiate aspiration of the fluidic material into the dispensing tip in response to determining the inconsistency. (Item 50) The at least one computing device further comprises: identifying the at least one reference line of the dispensing tip from the portion of the image of the dispensing tip; identifying a surface level of the fluid material within the dispensing tip in the image; determining a distance between the at least one reference line and the surface level; determining the volume of the fluid material by converting the distance to a volume of the fluid material based on correlation data, the correlation data including information about a correlation between a volume within the dispensing tip and distances from the at least one reference line to multiple surface levels within the dispensing tip; 50. The system of any of items 45-49, configured to: (Item 51) Item 51. The system of item 50, wherein the computing device is configured to determine the reference line based on pattern matching and / or segmentation of the captured image. (Item 52) 52. The system of any of items 50 and 51, wherein the computing device is configured to search for a pattern representing the reference line within the captured image. (Item 53) 53. The system of any of items 50-52, wherein the computing device is configured to compare at least a portion of the captured image with a reference image. (Item 54) Item 55. The system of item 53, wherein the computing device is configured to determine a match rate and / or a correlation value of the portion of the captured image and the reference image. 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 further comprises: determining a length of the first reference line in the image; determining a length of the second reference line in the image; determining an angle of a line relative to at least one of the first reference line and the second reference line, the line connecting a predetermined point on the first reference line and a predetermined point on the second reference line; determining the misalignment of the dispensing tip 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; adjusting the volume of the fluidic material based on the determination of the mismatch. 55. The system of any of items 45-54, configured to: (Item 56) 56. The system of any of items 45-55, wherein the misalignment of the dispensing tip includes a lateral misalignment and a depth misalignment. (Item 57) 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 further comprises: identifying a predetermined point of the first reference line within the image; identifying a predetermined point of the second reference line within the image; defining a matching line connecting the predetermined point of the first reference line and the predetermined point of the second reference line; determining an angle of the alignment line relative to at least one of the first reference line and the second reference line; comparing the angle to a threshold angle value; 57. The system of any of items 45-56, configured to perform the threshold angle value representing lateral misalignment of the dispensing tip. (Item 58) 58. The system of any of items 47-57, wherein the predetermined point of the first reference line is a center point of the first reference line in the image, and the predetermined point of the second reference line is a center point of the second reference line in the image. (Item 59) The system of any of items 57-58, wherein the system is configured to prevent the sample pipetting device from aspirating the fluidic material into the dispensing tip 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 the threshold angle value. (Item 60) The system of any of items 57-59, wherein the at least one computing device is further configured to flag suction of the fluid material into the dispensing tip and / or initiate suction of the 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 reference line and the second reference line meets and / or exceeds the threshold angle value. (Item 61) The at least one computing device further comprises: determining a length of the at least one reference line based on the captured image of the tip; obtaining an actual length of the at least one reference line; calculating a ratio between the length of the at least one reference line and the actual length of the at least one reference line; determining a depth mismatch of the dispensing tip based on the ratio; 61. The system of any of items 45-60, configured to: (Item 62) Item 62. The system of item 61, wherein the system is further configured to adjust the determined volume of the fluid material based on the ratio. (Item 63) a light source and a sample pipetting module; the light source and the image capture unit are attached to the sample pipetting module; and / or 63. The system of any of items 45-62, wherein the light source and the image capture unit are configured to move with the sample pipetting module so that an image of the dispensing tip can be captured at any position of the sample pipetting module. (Item 64) the sample pipetting device is configured to aspirate liquid into a further dispensing tip; the system is configured to determine a volume of the aspirated liquid; the image capture unit is configured to capture a further image of the further dispensing tip; 64. The system of any of items 45-63, wherein the computing device is configured to determine a pixel distance between reference points in the image associated with the further dispensing tip, and to correlate the determined volume with the determined pixel distance. (Item 65) Item 65. The system of item 64, wherein the computing device is configured to generate correlation data based on the determined volume and the determined pixel distance. (Item 66) Item 66. The system of item 65, wherein the correlation data is generated based on multiple correlations between multiple determined pixel distances and multiple determined volumes of liquid aspirated into the further dispensing tip. (Item 67) the aspirated liquid comprises a dye solution; and / or 67. The system of any of items 64-66, wherein the system is configured to determine the volume of the aspirated liquid based on spectrophotometry. (Item 68) 68. The system of any of items 64-67, wherein the system is configured to determine a mass of the aspirated liquid and to determine the volume of the aspirated liquid based on the determined mass of the aspirated liquid. (Item 69) 1. A method for evaluating a fluid substance in a container, comprising: capturing an image of at least a portion of the container using an image capture device; determining, using at least one computing device, a first reference line and a second reference line of the container from the image of the container; Determining at least one characteristic of at least one of the first reference line and the second reference line, the at least one characteristic comprises at least one of a length of the first reference line, a length of the second reference line, and an angle of a line relative to at least one of the first reference line and the second reference line; the line connecting a predetermined point on the first reference line and a predetermined point on the second reference line; comparing the at least one characteristic of at least one of the first reference line and the second reference line to a threshold value indicative of dispensing tip misalignment; A method comprising: (Item 70) Item 70. The method of item 69, wherein the first reference line and the second reference line are determined based on a pattern match and / or based on segmentation of the captured image. (Item 71) 71. The method of any of items 69 and 70, wherein determining the first reference line and the second reference line includes searching for a pattern representing the first reference line and / or the second reference line in the captured image. (Item 72) 72. The method of any of items 69-71, wherein determining the first reference line and the second reference line comprises comparing at least a portion of the captured image to a reference image. (Item 73) Item 73. The method of item 72, further comprising determining a match rate and / or correlation value of the portion of the captured image and the reference image. (Item 74) The container contains a fluidic material, and the method further comprises: identifying a surface level of the fluid material within the container in the captured image; determining a distance between at least one of the first reference line and the second reference line and the surface level; determining the volume of the fluid material by converting the distance to a volume of the fluid material based on correlation data, the correlation data including information about a correlation between a volume within the container and a distance from at least one of the first reference line and the second reference line to a plurality of surface levels within the container; 74. The method according to any one of items 69-73, comprising: (Item 75) The method further comprises: determining a length of the first reference line in the image; determining a length of the second reference line in the image; determining an angle of a line relative to at least one of the first reference line and the second reference line, the line connecting a predetermined point on the first reference line and a predetermined point on the second reference line; determining the misalignment of the container 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; adjusting the volume of the fluidic material based on the determination of the mismatch. 75. The method according to any one of items 69-74, comprising: (Item 76) 76. The method of any of items 69-75, wherein the inconsistencies of the container include a lateral inconsistency and a depth inconsistency. (Item 77) identifying a predetermined point of the first reference line within the image; identifying a predetermined point of the second reference line within the image; defining a matching line connecting the predetermined point of the first reference line and the predetermined point of the second reference line; determining an angle of the alignment line relative to at least one of the first reference line and the second reference line; comparing the angle to a threshold angle value, the threshold angle value representing lateral misalignment of the container; 77. The method of any of items 69-76, further comprising: (Item 78) Item 78. The method of item 77, wherein the predetermined point of the first reference line is a center point of the first reference line in the image, and the predetermined point of the second reference line is a center point of the second reference line in the image. (Item 79) 79. The method of any of items 77-78, further comprising preventing suction of the 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 meets and / or exceeds the threshold angle value. (Item 80) The method of any of items 77-79, further comprising a step of flagging suction of the fluid material into the container and / or a step of initiating suction of the 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 meets and / or exceeds the threshold angle value. (Item 81) determining a length of at least one of the first reference line and the second reference line based on the captured image of the container; obtaining an actual length of at least one of the first reference line and the second reference line; calculating a ratio between the length of at least one of the first and second reference lines and the actual length of the at least one of the first and second reference lines; determining a depth mismatch for the container based on the ratio; and 81. The method of any of items 69-80, further comprising: (Item 82) Item 82. The method of item 81, further comprising adjusting the determined volume of the fluid material based on the ratio. (Item 83) A computer program element that, when executed on a computing device of a system for evaluating a fluid substance, instructs said computing device to perform the steps of the method according to any of items 69-82. (Item 84) 84. A non-transitory computer-readable medium on which the computer program element according to item 83 is stored. (Item 85) 1. A system for evaluating a fluid substance, comprising: a container carriage device configured to support one or more containers; a sample pipetting device configured to dispense fluidic material in at least one of the containers on the container carriage device; and an image capture device configured to capture an image of at least one of the containers on the container carriage device; and at least one processing device; The system comprises: dispensing at least one fluidic substance into a container using the sample pipetting device; capturing an image of the container on the container carriage device using the image capture device; analyzing the image of the container using the at least one processing device to determine a volume of the dispensed at least one fluidic material in the container; analyzing the images of the container using the at least one processing device to determine a particle concentration of a total volume of fluid material in the container; A system configured to: (Item 86) Item 86. The system of item 85, wherein the total volume of fluidic material comprises at least one bodily fluid and / or at least one reagent. (Item 87) The system further comprises: capturing a first image of the container using the image capture device after dispensing a reagent into the at least one fluidic material contained in the container, the at least one fluidic material comprising at least one bodily fluid; capturing a second image of the container using the image capture device after adding and / or mixing the at least one fluidic substance and reagent in the container; analyzing the first image of the container using the at least one processing device to determine the volume of the dispensed reagent in the container; analyzing the second image of the container using the at least one processing device to determine a particle concentration of the entire volume of the fluid material in the container; 87. The system of any of items 85-86, configured to: (Item 88) 88. The system of any of items 85-87, wherein the particle concentration comprises a concentration of paramagnetic particles. (Item 89) 89. The system of any of items 85-88, wherein the at least one reagent comprises a chemiluminescent substrate. (Item 90) 90. The system of any of items 85-89, wherein the first image is captured approximately 0.2 seconds after the reagent is dispensed into the container and the second image is captured approximately 6.5 seconds after mixing. (Item 91) 91. The system of any of items 85-90, wherein the image capture device is mounted on the container carriage device, and the image capture device is configured and / or arranged to capture the image of the container from a side of the container. (Item 92) 92. The system of any of items 85-91, further comprising a light source, the light source and the image capture device being mounted on the container carriage device such that the light source is positioned opposite the image capture device. (Item 93) the container carriage device is a cleaning wheel having a rotatable plate; 93. The system of any of items 85-92, wherein the rotatable plate is configured to rotate the container to the image capture device. (Item 94) 94. The system of any of items 85-93, wherein the system is further configured to detect whether the container is present on the container carriage device. (Item 95) the at least one processing device determining a reference point within the image, the reference point being associated with the container; determining a surface level of the at least one fluid substance within the container in the image; determining the distance between the reference point and the surface level; converting the distance to a volume of the dispensed at least one fluidic material and / or reagent based on correlation data, the correlation data including information about a correlation between a volume within the container and distances from the reference point to a plurality of surface levels within the container; 95. The system of any of items 85-94, configured to: (Item 96) 96. The system of any of items 85-95, wherein determining a reference point includes determining a bottom portion of the container. (Item 97) 97. The system of any of items 95-96, wherein the distance is measured by pixel distance. (Item 98) 98. The system of any of items 95-97, wherein the processing device is configured to determine the reference points based on pattern matching and / or segmentation of the captured image. (Item 99) 99. The system of any of items 95 and 98, wherein the processing device is configured to search for a pattern representing the reference point within the captured image. (Item 100) 99. The system of claim 95, wherein the processing device is configured to compare at least a portion of the captured image with a reference image. (Item 101) Item 101. The system of item 100, wherein the processing device is configured to determine a match rate and / or a correlation value of the portion of the captured image and the reference image. (Item 102) the sample pipetting device is configured to aspirate liquid into a further container; the system is configured to determine a volume of the aspirated liquid; the image capture unit is configured to capture a further image of the further container; Item 85-101. The system of any of items 85-101, wherein the processing device is configured to determine a pixel distance between reference points in the image associated with the further container, and to correlate the determined volume with the determined pixel distance. (Item 103) Item 103. The system of item 102, wherein the processing device is configured to generate correlation data based on the determined volume and the determined pixel distance. (Item 104) Item 104. The system of item 103, wherein the correlation data is generated based on a plurality of correlations between a plurality of determined pixel distances and a plurality of determined volumes of liquid aspirated into the further container. (Item 105) the aspirated liquid comprises a dye solution; and / or 105. The system of any of items 102-104, wherein the system is configured to determine the volume of the aspirated liquid based on spectrophotometry. (Item 106) 106. The system of any of items 102-105, wherein the system is configured to determine a mass of the aspirated liquid and to determine the volume of the aspirated liquid based on the determined mass of the aspirated liquid. (Item 107) The at least one processing device further comprises: obtaining and / or determining the brightness of the entire volume of the fluid material from the image of the container; determining a particle concentration of the entire volume of the fluid material based on the brightness of the fluid material and calibration data; comparing the determined particle concentration to a threshold; flagging the container containing the entire volume of the fluid material in response to determining that the determined particle concentration is below the threshold; 107. The system of any of items 85-106, configured to: (Item 108) The system further comprises: aspirating at least a portion of the fluidic material from the container using the sample pipetting device; capturing a third image of at least a portion of the container using the image capture device; comparing the third image with a reference image using the at least one processing device; using the at least one processing device to determine a match score based on similarity between the third image and the reference image; comparing the generated match score to a threshold; 8. The system of any of items 85-107, configured to: (Item 109) The system further comprises: configured to determine an area of interest in the third image using the at least one processing device; Item 109. The system of any of items 85-108, wherein comparing the third image includes comparing the area of interest in the third image with at least a portion of the reference image. (Item 110) Item 110. The system of item 109, wherein the area of interest comprises a region adjacent to a bottom of the container. (Item 111) 111. The system of any of items 108-110, wherein the system is further configured to flag the result of the aspiration from the container when the match score is equal to and / or below the threshold value. (Item 112) the container carriage device includes a plurality of container slots, each container slot configured to support a container; The system further comprises: capturing a fourth image of one of the plurality of container slots at a first position of the container carriage device using the image capture device; comparing the fourth image with a reference image using the at least one processing device; using the at least one processing device to generate a match score based on similarity between the fourth image and the reference image; comparing the match score to a threshold; 112. The system of any of items 85-111, configured to: (Item 113) Item 113. The system of item 112, wherein the match score exceeding and / or meeting the threshold indicates the absence of the container in the one of the plurality of container slots. (Item 114) 114. The system of any of items 108-113, wherein the system is configured to remove the container from the one of the plurality of container slots when the match score is below the threshold. (Item 115) The system of any of items 108-114, wherein the system is configured to move the container carriage device to a second position after determining that the match score exceeds and / or meets a threshold. (Item 116) 1. A method for assessing a fluid substance in a container, comprising: Dispensing at least one fluidic substance into a container using a sample pipetting device; capturing an image of at least a portion of the container arranged on a container carriage device using an image capture device, the container carriage device being configured to support one or more containers; analyzing the image of the container using at least one computing device to determine a volume of the at least one dispensed fluidic material in the container; analyzing the images of the container using the at least one computing device to determine a particle concentration of a total volume of fluid material in the container; A method comprising: (Item 117) The step of capturing an image of the container comprises: capturing a first image of the container using the image capture device after dispensing a reagent into the at least one fluidic material contained in the container, the at least one fluidic material including at least one bodily fluid; capturing a second image of the container using the image capture device after mixing the added reagent with the at least one fluidic substance in the container; Including, analyzing the image of the container to determine the volume of the at least one dispensed fluidic material comprises analyzing the first image of the container to determine the volume of the dispensed reagent contained in the container; Item 117. The method of item 116, wherein analyzing the image of the container and determining the particle concentration of the entire volume of the fluid material includes analyzing the second image of the container and determining the particle concentration of the entire volume of the fluid material in the container. (Item 118) A computer program element that, when executed on a computing device of a system for evaluating a fluid substance, instructs the computing device to perform the steps of the method according to any of items 116-117. (Item 119) A non-transitory computer-readable medium having stored thereon the computer program elements of item 118. (Item 120) 1. A method for assessing a fluid substance in a container, comprising: Dispensing a fluidic substance into a container using a substance dispensing device; determining, using at least one computing device, a volume of the fluidic material in the container; receiving operational information of the material dispensing device, the operational information including operational parameters of the fluid material dispensing device; receiving a target dispense volume of the fluidic material; comparing the determined volume of the fluidic material to the target dispense volume; generating calibration information for the material dispensing device; adjusting the operating parameters of the material dispensing device based on the calibration information; A method comprising: (Item 121) Determining the volume of the fluid material comprises: capturing an image of at least a portion of the container using an image capture device; using at least one computing device to identify reference points within the image, the reference points being associated with the container; using the at least one computing device to identify a surface level of the fluid material within the container in the image; determining the distance between the reference point and the surface level; converting the distance to a volume of the fluid material based on correlation data, the correlation data including information about a correlation between a volume within the container and distances from the reference point to a plurality of surface levels within the container; Item 121. The method according to Item 120, comprising: (Item 122) providing the liquid to a further container; determining the volume of the dispensed liquid; capturing a further image of the container; determining pixel distances between reference points in the image associated with the further container; correlating the determined volume with the determined pixel distance; 122. The method of any of items 120-121, further comprising: (Item 123) Item 123. The method of item 122, further comprising generating correlation data based on the determined volume and the determined pixel distance. (Item 124) Item 124. The method according to item 123, wherein the correlation data is generated based on a plurality of correlations between a plurality of determined pixel distances and a plurality of determined volumes of liquid to be dispensed into the further container. (Item 125) the dispensed liquid comprises a dye solution; and / or 125. The method of any of items 122-124, wherein the volume of the dispensed liquid is determined spectrophotometrically. (Item 126) Item 126. The method of any of items 122-125, wherein determining the volume of the dispensed liquid comprises determining a mass of the dispensed liquid. (Item 127) aspirating at least a portion of the fluid material from the container; capturing an image of at least a portion of the container using an image capture device; comparing the image with a reference image; generating a match score based on the similarity between the image and the reference image; 127. The method of any of items 120-126, further comprising: (Item 128) comparing the match score to a threshold; and / or determining that the match score exceeds a threshold. Item 128. The method of item 127, further comprising: (Item 129) determining an area of interest within the image; Item 129. A method according to any of items 127-128, wherein the step of comparing the images comprises a step of comparing the area of interest in the image with at least a portion of the reference image. (Item 130) Item 130. The method of item 129, wherein the area of interest includes a region adjacent to the bottom of the container. (Item 131) 131. The method of any of items 127-130, further comprising the step of flagging the result of the aspiration from the container when the match score meets and / or falls below the threshold. (Item 132) arranging a plurality of containers within a plurality of container slots of a container carriage device; capturing an image of one of the plurality of container slots at a first position of the container carriage device using an image capture device; comparing the image with a reference image; generating a match score based on the similarity between the image and the reference image; 132. The method of any of items 127-131, further comprising: (Item 133) comparing the match score to a threshold; and / or determining whether the match score exceeds and / or meets a threshold, the match score exceeding the threshold indicating an absence of the container in the one of the plurality of container slots; Item 133. The method of item 132, further comprising: (Item 134) Item 134. The method of any of items 127-133, further comprising removing the container from the one of the plurality of container slots when the match score is below the threshold. (Item 135) Item 135. The method of any of items 127-134, further comprising the step of moving the container carriage device to a second position after determining that the match score exceeds and / or meets a threshold. (Item 136) A computer program element that, when executed on a computing device of a system for evaluating a fluid substance, instructs said computing device to perform the steps of the method according to any of items 120-135. (Item 137) A non-transitory computer-readable medium having stored thereon the computer program elements of item 136. [Brief explanation of the drawings]

[0165] [Figure 1] FIG. 1 is a block diagram of an exemplary instrument for analyzing biological samples.

[0166] [Figure 2] FIG. 2 illustrates a schematic diagram of an embodiment of the biological sample analysis instrument of FIG.

[0167] [Figure 3] FIG. 3 illustrates an example architecture of a computing device that can be used to implement aspects of the present disclosure.

[0168] [Figure 4] FIG. 4 is a schematic diagram illustrating an exemplary method for immunological analysis.

[0169] [Figure 5] FIG. 5 is a block diagram of an embodiment of the volumetric sensing system of FIG.

[0170] [Figure 6] FIG. 6 is a flowchart illustrating an exemplary method of operating a volumetric detection system.

[0171] [Figure 7]FIG. 7 is a flow chart illustrating an exemplary method for performing the operation of the volumetric detection system of FIG.

[0172] [Figure 8] FIG. 8 is a flowchart illustrating an exemplary method for operating the correlation data generation system to generate correlation data.

[0173] [Figure 9] FIG. 9 illustrates an embodiment of the dispensing tip volume detection device of FIG.

[0174] [Figure 10] FIG. 10 illustrates schematically an exemplary configuration of a sample aspiration system associated with a dispensing tip volume detection device.

[0175] [Figure 11] FIG. 11 is a perspective view of the sample aspiration system of FIG.

[0176] [Figure 12A] FIG. 12A is a side view of the sample aspiration system of FIG.

[0177] [Figure 12B] 12B is another side view of the sample aspiration system of FIG.

[0178] [Figure 13] FIG. 13 is a schematic perspective view of an exemplary dispensing tip.

[0179] [Figure 14] 14 is a cross-sectional view of the distal end of the dispensing tip of FIG. 13.

[0180] [Figure 15] FIG. 15 is a flow chart illustrating an exemplary method of operating a dispensing tip volume detection device.

[0181] [Figure 16] FIG. 16 is a flow chart illustrating an exemplary method for performing the operation of the dispensing tip volume detection device of FIG.

[0182] [Figure 17] FIG. 17 illustrates an exemplary analysis of a captured image of a dispensing tip.

[0183] [Figure 18] FIG. 18 illustrates an analysis of the captured image of FIG.

[0184] [Figure 19] FIG. 19 illustrates an analysis of the captured image of FIG.

[0185] [Figure 20] FIG. 20 is an exemplary correlation curve corresponding to tip volume correlation data.

[0186] [Figure 21] FIG. 21 is a flowchart illustrating an exemplary method for operating the tip volume correlation data generation system to generate tip volume correlation data.

[0187] [Figure 22] FIG. 22 illustrates an embodiment of the container volume detection device of FIG.

[0188] [Figure 23] FIG. 23 illustrates an exemplary container carriage device that includes a container volume detection device.

[0189] [Figure 24] 24 is another perspective view of the container carriage device of FIG. 23 illustrating the container image capture unit of FIG. 23.

[0190] [Figure 25] FIG. 25 is a top view of a cleaning wheel with a container volume detection device including a container image capture unit.

[0191] [Figure 26] FIG. 26 is a flow chart illustrating an exemplary method of operating a container volume detection device in conjunction with a cleaning wheel.

[0192] [Figure 27] FIG. 27 is a flow chart illustrating an exemplary method of operating a reaction vessel dispensing volume detection device of a vessel volume detection device.

[0193] [Figure 28] FIG. 28 is a flow chart illustrating an exemplary method for performing the operation of the reaction vessel dispense volume detection device of FIG.

[0194] [Figure 29] FIG. 29 illustrates an exemplary analysis of a captured image of a reaction vessel.

[0195] [Figure 30] FIG. 30 is an exemplary correlation curve corresponding to the container volume correlation data.

[0196] [Figure 31] FIG. 31 is a flowchart illustrating an exemplary method for operating a container volume correlation data generation system to generate container volume correlation data.

[0197] [Figure 32] FIG. 32 is a flow chart illustrating an exemplary method of operating a reaction vessel residual volume detection device of a vessel volume detection device.

[0198] [Figure 33] FIG. 33 is a flow chart illustrating an exemplary method for performing the operation of the reaction vessel residual volume detection device of FIG.

[0199] [Figure 34]FIG. 34 illustrates an exemplary analysis of a captured image of a container.

[0200] [Figure 35] FIG. 35 is a block diagram of an exemplary system in which the dispense adjustment device of the container volume detection device is operated.

[0201] [Figure 36] 36 is a flowchart illustrating an exemplary method for operating the dispense regulation device of FIG. 35.

[0202] [Figure 37] FIG. 37 is a flow chart illustrating an exemplary method of operating a reaction vessel detection device of a vessel volume detection device.

[0203] [Figure 38] FIG. 38 is a flow chart illustrating an exemplary method for performing the operation of the reaction vessel detection device of FIG.

[0204] [Figure 39] FIG. 39 illustrates an exemplary analysis of captured images of container slots on a cleaning wheel.

[0205] [Figure 40] FIG. 40 is a block diagram of the exemplary integrity assessment system of FIG.

[0206] [Figure 41] FIG. 41 is a block diagram of the exemplary dispensing tip integrity assessment device of FIG.

[0207] [Figure 42] FIG. 42 illustrates an exemplary sample quality detection device.

[0208] [Figure 43] FIG. 43 is a flow chart illustrating an exemplary method for operating the sample quality detection device of FIG.

[0209] [Figure 44] FIG. 44 is a flowchart illustrating an exemplary method of operating the image assessment device of FIG.

[0210] [Figure 45] FIG. 45 illustrates an exemplary analysis of a captured image.

[0211] [Figure 46] FIG. 46 is a flowchart illustrating an exemplary method for finding regions of interest within an image.

[0212] [Figure 47] FIG. 47 is a flowchart of an exemplary method for extracting color parameters of an image.

[0213] [Figure 48] FIG. 48 illustrates an example histogram of an image.

[0214] [Figure 49] FIG. 49 is a flowchart of an exemplary method for operating the classification data generation device of FIG.

[0215] [Figure 50] FIG. 50 is an exemplary table of interferent values being analyzed into classification labels.

[0216] [Figure 51] FIG. 51 is an exemplary set of sample classification identifiers.

[0217] [Figure 52] FIG. 52 illustrates an exemplary color parameter data table for three interferents.

[0218] [Figure 53]FIG. 53 shows an exemplary set of sample classifiers from a combination of first, second, and third interferents as shown in FIG.

[0219] [Figure 54] FIG. 54 is a block diagram that schematically illustrates the exemplary sorting device of FIG.

[0220] [Figure 55] FIG. 55 is an exemplary dataset of sample classification results and associated flagging results.

[0221] [Figure 56] FIG. 56 is a block diagram of an exemplary tip alignment detection device.

[0222] [Figure 57] FIG. 57 is a cross-sectional view of an exemplary dispensing tip illustrating possible tolerances in the dispensing tip.

[0223] [Figure 58] FIG. 58 schematically illustrates an exemplary misalignment of a dispensing tip.

[0224] [Figure 59] FIG. 59 illustrates possible types of misalignment of the dispensing tip.

[0225] [Figure 60] Figure 60A is a cross-sectional side view of an exemplary dispensing tip that can be used with a tip alignment detection device; Figure 60B is a close-up view of a portion of the dispensing tip of Figure 60A; and Figure 60C is a close-up view of a portion of the dispensing tip of Figure 60A.

[0226] [Figure 61] FIG. 61 is a flowchart illustrating an exemplary method for assessing dispense tip alignment.

[0227] [Figure 62]FIG. 62 is a flow chart illustrating an exemplary method for detecting dispense tip misalignment.

[0228] [Figure 63] FIG. 63 is a flow chart illustrating another exemplary method for detecting dispense tip misalignment.

[0229] [Figure 64] FIG. 64 schematically illustrates an example image showing lateral misalignment of a dispensing tip.

[0230] [Figure 65] FIG. 65 is a flowchart illustrating an exemplary method for correcting volume using a second reference line.

[0231] [Figure 66] FIG. 66 is a flowchart illustrating another exemplary method for correcting volume using a second reference line.

[0232] [Figure 67] FIG. 67 schematically illustrates depth misalignment of the dispensing tip relative to the camera unit.

[0233] [Figure 68] FIG. 68 is an exemplary data table of volume detection before and after correction performed by the tip alignment detection device.

[0234] [Figure 69] FIG. 69 is a block diagram of the exemplary particle concentration checking system of FIG.

[0235] [Figure 70] FIG. 70 shows example images of reaction vessels with different particle concentrations.

[0236] [Figure 71] FIG. 71 is a block diagram of an exemplary reaction vessel particle concentration check system.

[0237] [Figure 72] FIG. 72 is a flow chart illustrating an exemplary method for measuring particle concentration in a fluid material contained within a reaction vessel.

[0238] [Figure 73] FIG. 73 is a flowchart illustrating an exemplary method for generating calibration data.

[0239] [Figure 74] FIG. 74 is a table of exemplary materials used to generate the calibration data.

[0240] [Figure 75] FIG. 75 shows an exemplary calibration curve plotted from the calibration data.

[0241] [Figure 76] FIG. 76 is a flow chart illustrating an exemplary method for measuring particle concentration in a fluid material contained within a reaction vessel.

[0242] [Figure 77] FIG. 77 is an exemplary table of exemplary concentration thresholds for different calibrators.

[0243] [Figure 78] FIG. 78 is a flow chart of an exemplary diagnostic function utilizing the capabilities of the reaction vessel particle concentration check system.

[0244] [Figure 79] FIG. 79 is a flow chart of an alternative embodiment of the diagnostic function of FIG. DETAILED DESCRIPTION OF THE INVENTION

[0245] Various embodiments will be described in detail with reference to the drawings, in which like reference numerals represent like parts and assemblies throughout the several views. Reference to various embodiments does not limit the scope of the claims appended hereto. Additionally, any examples described herein are not intended to be limiting, but merely describe some of the many possible embodiments of the appended claims.

[0246] FIG. 1 is a block diagram of an exemplary instrument 100 for analyzing biological samples. In some embodiments, the 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 instrument 100 system and include a dispensing tip 112 and a vessel 114. Also shown are one or more container carriage devices 116 provided within the instrument 100. Additionally, the preparation evaluation system 104 includes a volume detection system 120, a dispensing tip evaluation system 122, and a carriage detection system 126. In some embodiments, the volume detection system 120 utilizes a dispensing tip image capture unit 130 and a vessel 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 check system 124 uses the vessel image capture unit 132. In some embodiments, the carriage detection system 126 uses the carriage image capture unit 134.

[0247] It should be noted that the systems for evaluating a fluid substance according to the fourth, fifth, and / or ninth aspects, as described in the Summary section of this disclosure, may each refer to an apparatus 100 for analyzing a biological sample, and / or each may refer to one or more components and / or devices of the apparatus 100. Furthermore, the methods for evaluating a fluid substance according to the first, sixth, tenth, and / or thirteenth aspects, as described in the Summary section of this disclosure, may each refer to a method for operating the apparatus 100, and / or each may refer to a method for operating one or more components and / or devices of the apparatus 100.

[0248] The biological sample analysis instrument 100 operates to analyze biological samples for a variety of purposes. In some embodiments, the biological sample analysis instrument 100 is configured to analyze blood samples and operates to collect, test, process, store, and / or transfuse blood and its components.

[0249] The material preparation system 102 operates to prepare one or more materials for further analysis by the material evaluation system 106. In some embodiments, the material preparation system 102 operates to aliquot material 118 using a container 110, aspirate material 118 from the container 110, and dispense material 118 into the container 110.

[0250] The preparation evaluation system 104 operates to evaluate the preparation of a substance for subsequent analysis by the substance evaluation system 106. In some embodiments, the preparation evaluation 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 evaluation 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 so that the substance evaluation system 106 can produce reliable results using the substance 118.

[0251] The substance evaluation system 106 operates to evaluate the substance 118 prepared by the substance preparation system 102. As an example, the substance evaluation system 106 performs an immunoassay such as that described with reference to FIG.

[0252] The container 110 is used to prepare one or more substances 118 that are analyzed by the substance evaluation system 106. The container 110 can be of various types, such as a specimen tube (also referred to herein as a sample tube), a pipetting tip, and a vessel. In some embodiments, the container 110 includes a dispensing tip 112 and a vessel 114.

[0253] A dispensing tip 112 is provided in the material preparation system 102 to aliquot or aspirate a substance 118 from another container, such as a vessel 114. For example, the dispensing tip 112 is used to aliquot a sample from a sample tube or aspirate a sample or reagent from a sample or reagent vessel. Examples of the dispensing tip 112 are described and illustrated in further detail with reference to Figures 13 and 14.

[0254] Containers 114 are provided to the material preparation system 102 to contain substances 118 for preparation and analysis. In some embodiments, the material preparation system 102 dispenses the substances 118 into the containers 114. Examples of containers 114 include sample containers, diluent containers, and reaction containers, which are described in further detail herein.

[0255] The container carriage device 116 is configured to hold and carry the container 110 at various locations within the instrument 100 such that the material preparation system 102, the preparation evaluation system 104, and the material evaluation system 106 use the container 110 in various ways. Examples of the container carriage device 116 include vessel racks (e.g., sample racks, reagent racks, and diluent racks), sample presentation units, vessel carriage units (e.g., sample carriage units, reaction vessel carriage units, and reagent carriage units), vessel transfer units (e.g., sample transfer units, reagent transfer units, incubator transfer units, and reaction vessel transfer units), and vessel holding plates or wheels (e.g., sample wheels, incubator wheels, and wash wheels), which are described and illustrated in further detail with reference to FIG.

[0256] Substance 118 is prepared, evaluated, and tested for various tests and analyses within instrument 100. Substance 118 includes any substance that can be aliquoted, aspirated, and dispensed within 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.

[0257] The volume detection system 120 of the preparation evaluation system 104 operates to detect the volume of the fluidic substance 118 in the container 110 and determine whether the volume held in the container 110 is suitable as a target. As described herein, the volume detection system 120 is configured to detect the volume at the dispensing tip 112 using a dispensing tip image capture unit 130 and the volume at the container 114 using a container image capture unit 132.

[0258] The dispensing tip evaluation system 122 of the preparation evaluation system 104 operates to evaluate the integrity of the fluidic material 118. In some embodiments, the dispensing tip evaluation system 122 detects any interfering substances that may interfere with the analytical procedure and produce inaccurate results. As described herein, the dispensing tip evaluation system 122 is configured to use the dispensing tip image capture unit 130 to determine the quality of the fluidic material 118 in the dispensing tip 112 and the alignment of the dispensing tip 112 with respect to the dispensing tip image capture unit 130.

[0259] The particle concentration check system 124 operates to determine particle concentrations in fluidic materials contained in vessels, such as reaction vessels, sample vessels, dilution vessels, cuvettes, or any suitable type of vessel used throughout the processes in the instrument 100. In some embodiments, the reaction vessel particle concentration check system 1700 uses a vessel image capture unit 132.

[0260] The dispensing tip image capture unit 130 operates to capture images of the dispensing tip 112 at one or more locations. In some embodiments, the dispensing tip image capture unit 130 is fixed at a specific location within the instrument 100. In other embodiments, the dispensing tip image capture unit 130 is movably positioned within the instrument 100, capable of moving either independently from 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 dispensing tip image capture units 130. As described herein, the dispensing tip image capture unit 130 can include a camera unit 550 (e.g., FIG. 11 ) and a camera unit 2550 (FIGS. 11 and 67 ).

[0261] The container image capture unit 132 operates to capture images of the container 114 at one or more locations. In some embodiments, the container image capture unit 132 is fixed at a specific location within the instrument 100. In other embodiments, the container image capture unit 132 is movably disposed within the instrument 100, capable of moving either 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 image capture units 132. As described herein, the container tip image capture unit 132 includes a camera unit 730 (e.g., FIG. 24 ).

[0262] The carriage image capture unit 134 operates to capture images of the container carriage device 116 with or without the container 110 at one or more locations. In some embodiments, the carriage image capture unit 134 is fixed at a specific location within the instrument 100. In other embodiments, the carriage image capture unit 134 is movably disposed within the instrument 100, capable of moving either 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 carriage image capture units 134.

[0263] 1, in some embodiments, the appliance 100 operates to communicate with the management system 136 via a data communications network 138. For example, the appliance 100 includes a communications device (such as communications device 246 of FIG. 3 ) through which the appliance 100 communicates with the management system 136.

[0264] In some embodiments, the management system 136 is located remotely from the instrument 100 and is configured to perform diagnostics based on data from the instrument 100. In addition, the instrument 100 can evaluate instrument performance and generate reports. One example of the management system 136 includes one or more computing devices running the PRO Services remote service application available from Beckman Coulter, Inc. (Brea, CA).

[0265] The Beckman Coulter PRO Services remote service application can provide a secure, continuous connection between the biological sample analysis instrument 100 and a remote diagnostic command center (e.g., management system 136) via a network (e.g., network 138). The biological sample analysis instrument 100 may be connected to the remote diagnostic command center by the Internet, via an Ethernet port, Wi-Fi, or a cellular network.

[0266] Still referring to FIG. 1 , data communications network 138 communicates 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 and wide area networks, such as the Internet. In some embodiments, network 138 includes a wireless communications system, a wired communications system, or a combination of wireless and wired communications systems. Wired communications systems, in various possible embodiments, can transmit data using electrical or optical signals. Wireless communications systems typically transmit signals via electromagnetic waves, such as in the form of optical or radio frequency (RF) signals. Wireless communications systems typically include an optical or RF transmitter for transmitting the optical or RF signals and an optical or RF receiver for receiving the optical or RF signals. Examples of wireless communications systems include Wi-Fi communications devices (such as using a wireless router or wireless access point), cellular communications devices (such as using one or more cellular base stations), and other wireless communications devices.

[0267] 2 schematically illustrates an example of the biological sample analysis instrument 100 of FIG. 1. In the illustrated example, the instrument 100 is configured as an immunoassay analyzer. As described above, the 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 board 140, a sample presentation unit 142, a reaction vessel feeder 144, a reaction vessel carriage unit 146, a sample transfer unit 148, a pipetting tip feeder 150, a sample pipetting device 152, a sample wheel 158, a reagent carriage unit 160, a reagent pipetting device 162, a reagent storage device 164, a reagent loading device 166, an incubator-transfer unit 170, an incubator 172, a reaction vessel transfer unit 174, a wash wheel 176, and a substrate loading device 180. In some embodiments, the material evaluation system 106 includes an optical measurement device 190 and an evaluation processing device 192. Some embodiments of the material evaluation system 106 are further associated with at least some operations performed by the incubator-transfer unit 170, the incubator 172, the reaction vessel-transfer unit 174, the wash wheel 176, and the substrate loading device 180.

[0268] The sample supply board 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 racks of sample tubes onto the sample supply board 140. The sample supply board 140 can move the racks to the sample presentation unit 142 for pipetting and receives the pipetted racks, which are returned by the sample presentation unit 142 after pipetting.

[0269] The sample presentation unit 142 operates to transport one or more racks of sample tubes to a designated location. In some embodiments, the sample supply board 140 operates to provide a single sample rack to the sample presentation unit 142. Additionally, the sample presentation unit 142 can operate to identify the rack and the sample ID on the rack. The sample presentation unit 142 transports the rack to a sample pipetting location where a sample pipettor aliquots from one of the sample tubes in the rack. When the sample pipettor aliquots from one of the sample tubes in the rack, the sample presentation unit 142 sends another sample tube in the rack for the next pipetting operation. After all of the sample tubes have been pipetted, the sample presentation unit 142 returns the rack to the sample supply board 140. The sample presentation unit 142 can include a sample rack presentation unit. In other embodiments, the sample presentation unit 142 is configured to transport a puck carrying a single tube. It is understood that the sample presentation unit 142 can also be configured and used for other types of containers, such as cups or vessels.

[0270] Reaction vessel feeder 144 feeds a plurality of reaction vessels to reaction vessel carriage unit 146. A user can load a large number of new, empty reaction vessels into reaction vessel feeder 144. In some embodiments, reaction vessel feeder 144 operates to orient the reaction vessels as they are fed into reaction vessel carriage unit 146.

[0271] The reaction vessel carriage unit 146 operates to transfer reaction vessels from the reaction vessel feeder 144 to the sample transfer unit 148. In some embodiments, the reaction vessel carriage unit 146 picks up one or more reaction vessels from the reaction vessel feeder 144 and transfers the reaction vessels to the sample transfer unit 148.

[0272] The sample transfer unit 148 operates to transfer empty reaction vessels from the reaction vessel carriage unit 146 to the sample wheel 158 and the reagent carriage unit 160. Additionally, the sample transfer unit 148 operates to transfer aliquoted sample vessels to the reagent carriage unit 160 and to transfer sample vessels from the reagent carriage unit 160 back to the sample wheel 158. The sample transfer unit 148 can also operate to dispose of sample vessels and diluent vessels that have been used in a predetermined process.

[0273] The pipetting tip feeder 150 supplies pipetting tips to the sample pipetting device 152. In this document, the pipetting tips are examples of dispensing tips 112 and therefore may also be referred to herein as dispensing tips 112. In some embodiments, a plurality of pipetting tips in a rack are loaded into an array in the pipetting tip feeder 150. The pipetting tips are transferred to and engaged with the sample pipetting device 152 for pipetting. Once used, the pipetting tips are disengaged from the sample pipetting device 152 for disposal, and the sample pipetting device 152 can return to the pipetting tip feeder 150. The user can discard solid waste, including the used pipetting tips.

[0274] The sample pipetting device 152 performs various pipetting operations. The sample pipetting device 152 receives pipetting tips from the pipetting tip feeder 150 and engages the pipetting tips with the sample pipetting device 152. In some embodiments, the sample pipetting device 152 engages the pipetting tips by pushing the pipette mandrel into the pipetting tip and lifting the pipette mandrel that fits into the pipetting tip. As described herein, some embodiments of pipetting tips are disposable after a single use or multiple uses.

[0275] In some embodiments, the sample pipetting device 152 includes a sample aliquot pipetting unit ("sample aliquot gantry") 152A and a sample precision pipetting unit ("sample precision gantry") 152B.

[0276] The sample aliquot pipetting unit 152A operates to pipette aliquots of sample from sample tubes located in the sample presentation unit 142 and dispense the aliquots of sample into sample containers on the sample wheel 158. The sample aliquot pipetting unit can dispose of used pipetting tips when pipetting is completed for each sample. As described herein, the sample aliquot pipetting unit 152A can include a camera unit 550, further described herein with reference to, for example, Figures 11, 12A, and 12B.

[0277] The sample precision pipetting unit 152B operates to pipette a sample from a sample container located on the reagent carriage unit 160. The sample precision pipetting unit can then dispense the sample into a reaction container. In some embodiments, the sample can be first dispensed into a dilution container (e.g., with a wash buffer provided by the reagent pipetting device 162) to create a sample dilution before being dispensed into the reaction container. The sample precision pipetting unit can dispose of used pipetting tips when the pre-determined test is completed. As described herein, the sample precision pipetting unit 152B can include a camera unit 2550, further described herein with reference to FIGS. 11, 12A, 12B, and 67.

[0278] The sample wheel 158 stores aliquots of sample in sample containers thereon. In some embodiments, the sample wheel 158 operates to maintain the sample at a lower temperature, such as about 4-10° C., to reduce analyte concentrations that are altered by evaporation. The sample containers can be transferred back to the sample wheel 158 after reagent pipetting if additional testing is required.

[0279] The reagent carriage unit 160 is configured to support multiple containers and transport the containers to different locations. In some embodiments, the reagent carriage unit 160 is configured to hold a plurality of four containers (e.g., three or four containers) that can be used simultaneously per reagent pipettor of the reagent pipetting device 162. In some embodiments, the reagent carriage unit 160 is thermally controlled at approximately 30°C to 40°C. In other embodiments, the reagent carriage unit 160 is maintained at approximately 37°C, for example, to ensure consistent kinetic reaction of enzymes.

[0280] In some embodiments, the reagent carriage unit 160 is configured to hold reaction vessels, dilution vessels, and sample vessels and transport the vessels for sample and reagent pipetting. In some embodiments, the reagent carriage unit 160 includes a carriage shuttle that is movable along a predetermined path. For example, the reagent carriage unit 160 is moved proximate to the sample transfer unit 148 to receive reaction vessels, dilution vessels, and sample vessels from the sample transfer unit 148. Furthermore, the reagent carriage unit 160 can move to the reagent pipetting device 162 to pipette reagents and to the sample precision pipetting unit 152B to pipette samples. In some embodiments, the reagent carriage unit 160 moves to the sample transfer unit 148 to remove dilution vessels and sample vessels, and to the culture transfer unit 170 to remove reaction vessels.

[0281] The reagent pipetting device 162 operates to pipette reagents from a reagent storage device 164 into reaction vessels on the reagent carriage unit 160. In some embodiments, the reagent pipetting device 162 includes multiple pipettors that can pipette different tests simultaneously to support throughput. In some embodiments, the reagent pipetting device 162 is thermally controlled at approximately 30°C to 40°C. In other embodiments, the reagent pipetting device 162 is maintained at approximately 37°C to ensure consistent binding kinetics, for example, for enzymatic reactions.

[0282] The reagent storage device 164 stores reagents. The reagent storage device includes a reagent transfer unit configured to transfer reagent packs to predetermined locations. In some embodiments, the reagent storage device 164 can transfer reagent packs from the reagent loading device 166 to the reagent storage device 164, from the reagent storage device 164 to a pipetting location for pipetting by the reagent pipetting device 162, from the pipetting location to the reagent storage device 164, from the pipetting location to a waste location when the reagent is consumed, from the reagent storage device 164 to a waste location when the reagent expires, and from the reagent storage device 164 to the reagent loading device 166 for unloading the reagent pack. In some embodiments, the reagent storage device 164 is thermally controlled at approximately 2°C to 15°C. In other embodiments, the reagent storage device 164 is maintained at approximately 4°C to 10°C.

[0283] The reagent loading device 166 operates to load one or more reagent packs. A user can load the reagent packs into the reagent loading device 166.

[0284] The incubator-transport unit 170 transports reaction vessels to and from the incubator 172. In some embodiments, the incubator-transport unit 170 transports one or more of the pipetted reaction vessels from the reagent carriage unit 160 to the incubator 172. Additionally, the incubator-transport unit 170 can transport one or more reaction vessels from the incubator 172 to the reagent carriage unit 160. The incubator-transport unit 170 can also remove read or completed reaction vessels from the incubator 172.

[0285] 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, immunological and enzymatic reactions. As an example, incubator 172 performs assay incubations.

[0286] Reaction vessel transfer unit 174 transfers reaction vessels to and from incubator 172. In some embodiments, reaction vessel transfer unit 174 transfers incubated reaction vessels from incubator 172 to wash wheel 176, transfers assay reaction vessels from wash wheel 176 to incubator 172, transfers reaction vessels containing substrate from wash wheel 176 to incubator 172 for substrate incubation or enzymatic reaction, transfers washed reaction vessels from incubator 172 to optical measurement device 190 after substrate incubation, and transfers read or completed reaction vessels from optical measurement device 190 to incubator 172. Used reaction vessels can be delivered to a disposal location.

[0287] The wash wheel 176 receives and supports reaction vessels thereon so that various aspects of the diagnostic process can be performed using the material evaluation system 106. Examples of the wash wheel 176 are described and illustrated in further detail with reference to Figures 23-25. In some embodiments, the wash wheel 176 is a thermally controlled device that separates bound or free analyte from particles after incubation. In some embodiments, the wash wheel 176 is maintained at approximately 30°C to 40°C. In other embodiments, the wash wheel 176 is maintained at approximately 37°C, for example, to ensure enzymatic reactions.

[0288] The substrate pipetting device 178 operates to dispense substrate into the washed reaction vessel. One example of a substrate is a chemiluminescent substrate for an immunoassay enzyme reaction, such as Lumi-Phos 530, which can produce light to provide detection corresponding to the quantity of analyte captured on the magnetic particles.

[0289] The substrate loading device 180 operates to load one or more substrates from a supply. In some embodiments, the substrate loading device 180 includes a set of two bottles, one of which is in use and the other of which is arranged for an unloading and new loading process. The substrate pipetting device 178 can operate to draw substrate from the bottle in use.

[0290] Light measurement device 190 operates to detect and measure light resulting from the immunoassay (e.g., light L in FIG. 4). In some embodiments, light measurement device 190, which may also be referred to as a luminometer, includes a light-tight enclosure containing a photomultiplier tube (PMT) for reading the magnitude of chemiluminescence from a reaction vessel containing a substrate. Reaction vessels can be transferred to and removed from light measurement device 190 by reaction vessel transfer unit 174.

[0291] The evaluation processing device 192 operates to receive information about the amount of light detected by the light measurement device 190 and evaluate the analysis based on the information.

[0292] 3 illustrates an example architecture of a computing device that can be used to implement aspects of the present disclosure, including the biological sample analysis instrument 100 or various systems of the instrument 100, such as the material preparation system 102, the preparation evaluation system 104, and the material evaluation system 106. Furthermore, one or more devices or units included in the systems of the instrument 100 can also be implemented with at least some components of a computing device, as illustrated in FIG. 3. Such a computing device is designated herein as reference numeral 200. The computing device 200 is used to execute the operating system, application programs, and software modules (including the software engine) described herein.

[0293] Computing device 200, in some embodiments, includes at least one processing device 202, such as a central processing unit (CPU). Various processing devices are available from various manufacturers, e.g., Intel or Advanced Micro Devices. In this example, computing device 200 also includes a system memory 204 and a system bus 206 that couples various system components, including system memory 204, to processing device 202. System bus 206 may be one of any number of types of bus structures, including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures.

[0294] Examples of computing devices suitable for computing device 200 include a desktop computer, a laptop computer, a tablet computer, a mobile device (such as a smartphone, an iPod® mobile digital device, or other mobile device), or other device configured to process digital instructions.

[0295] The system memory 204 includes a read-only memory 208 and a random access memory 210. A basic input / output system 212, containing the basic routines that act to transfer information within the computing device 200, such as during start-up, is typically stored in the read-only memory 208.

[0296] Computing device 200 also includes a secondary storage device 214, such as a hard disk drive in some embodiments, for storing digital data. The secondary storage device 214 is connected to system bus 206 by a secondary storage interface 216. The secondary storage devices and their associated computer-readable media provide non-volatile storage of computer-readable instructions (including application programs and program modules), data structures, and other data for computing device 200.

[0297] Although the exemplary environment described herein employs a hard disk drive as the 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 cassettes, flash memory cards, digital video disks, Bernoulli cartridges, compact disk read-only memories, digital versatile disk read-only memories, random access memories, or read-only memories. Some embodiments include non-transitory media.

[0298] A number of program modules may be stored in the secondary storage device 214 or in memory 204, including an operating system 218, one or more application programs 220, other program modules 222, and program data 224.

[0299] In some embodiments, computing device 200 includes input devices that allow a user to provide input to computing device 200. Examples of input devices 226 include a keyboard 228, a pointer input device 230, a microphone 232, and a touch-sensitive display 240. Other embodiments include other input devices 226. Input devices are often connected to processing device 202 through an input / output interface 238 that is coupled to system bus 206. These input devices 226 can be connected by any number of input / output interfaces, such as a parallel port, a serial port, a game port, or a universal serial bus. Wireless communication between the input devices and interface 238 is also possible, and in some possible embodiments includes infrared, BLUETOOTH® wireless technology, WiFi technology (such as 802.11a / b / g / n), cellular, or other radio frequency communication systems.

[0300] In the exemplary embodiment, touch-sensitive display device 240 is also connected to system bus 206 via an interface, such as video adapter 242. Touch-sensitive display device 240 includes a touch sensor for receiving input from a user when the user touches the display. Such a sensor can be a capacitive sensor, a pressure sensor, or other touch sensor. The sensor detects not only contact with the display, but also the location of the contact and the movement of the contact over time. For example, a user can move a finger or stylus across the screen to provide written input. The written input is evaluated and, in some embodiments, converted into text input.

[0301] In addition to display device 240, computing device 200 may include various other peripheral devices (not shown), such as speakers or printers.

[0302] Computing device 200 further includes a communications device 246 configured to establish communications across a network. In some embodiments, when used in a local area networking environment or a wide area networking environment (such as the Internet), computing device 200 typically connects to the network through a network interface, such as wireless network interface 248. Other possible embodiments use other wired and / or wireless communications devices. For example, some embodiments of computing device 200 include an Ethernet network interface or a modem for communicating across the network. In still other embodiments, communications device 246 is capable of short-range wireless communications. Short-range wireless communications are one-way or two-way short- to medium-range wireless communications. Short-range wireless communications can be established according to various technologies and protocols. Examples of short-range wireless communications include radio frequency identification (RFID), near field communications (NFC), Bluetooth technology, and Wi-Fi technology.

[0303] Computing device 200 typically includes at least some form of computer-readable media. Computer-readable media includes any available media that can be accessed by computing device 200. By way of example, computer-readable media include computer-readable storage media and computer-readable communication media.

[0304] Computer-readable storage media include volatile and nonvolatile, removable and non-removable media implemented in any device configured to store information, such as computer-readable instructions, data structures, program modules, or other data, including, but not limited to, random access memory, read-only memory, electrically erasable programmable read-only memory, flash memory or other memory technology, compact disc read-only memory, digital versatile disks or other optical storage devices, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed by computing device 200.

[0305] Computer-readable communication media typically embodies computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. The term "modulated data signal" refers to a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, computer-readable communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency, infrared and other wireless media. Combinations of any of the above are also included within the scope of computer-readable media.

[0306] Blood samples include whole blood, serum, plasma, and other blood components or fractions. In some embodiments, the biological sample analysis instrument 100 is configured to analyze one or more bodily fluid sample types. The bodily fluids are 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 at, but not limited to, donor centers, physicians' offices, phlebotomist offices, hospitals, clinics, and other medical settings. The collected bodily fluids and their components are then often processed, tested, and distributed in or through clinical laboratories, hospitals, blood banks, physicians' offices, or other medical settings. In this disclosure, the instrument 100 is primarily described as performing immunoassays, which measure the presence or concentration of macromolecules in a solution through the use of antibodies or immunoglobulins. Such macromolecules are also referred to herein as analytes. In other embodiments, however, the instrument 100 includes any type of biological sample analyzer. For example, the instrument 100 can be a clinical chemistry analyzer, a blood typing analyzer, a nucleic acid analyzer, a microbiology analyzer, or any other type of in vitro diagnostic (IVD) analyzer.

[0307] 4 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 substance preparation system 102, preparation evaluation system 104, and / or substance evaluation system 106 of instrument 100.

[0308] In operation 302, a cuvette 320 (e.g., a reaction vessel) is transported to a predetermined location and a first reagent including magnetic particles 322 is dispensed into the cuvette 320. In some embodiments, the cuvette 320 is a reaction vessel and is transported to the wash wheel 176.

[0309] In operation 304, a sample or specimen 324 is dispensed into a cuvette 320. In some embodiments, a sample pipetting device 152, engaged with a pipetting tip provided by a pipetting tip feeder 150, aspirates the sample 324 from a sample container transported to a predetermined location. Once the sample has been dispensed into the cuvette 320, the cuvette 320 may undergo mixing, if required, to produce magnetic particle carriers formed of the antigens and magnetic particles in the sample 324 bound together, respectively.

[0310] In operation 306, the cuvette 320 undergoes a first washing process in which the magnetic particle carriers are magnetically collected by a magnetic collection unit 326 and a binding-releasing separation is performed by a binding-releasing washing suction nozzle 328. As a result, unreacted materials 330 in the cuvette 320 are removed.

[0311] In operation 308, a second reagent 332, such as a labeled reagent containing a labeled antibody, is dispensed into the cuvette 320. As a result, immune complexes 334 are produced, each formed of the bound magnetic particle carrier and the labeled antibody 332.

[0312] In operation 310, a second bind-release wash process is performed to magnetically collect the magnetic particle carriers by the magnetic collection structure 336. Further, bind-release separation is performed by the bind-release wash suction nozzle 338. As a result, the labeled antibody 332 that is not bound to the magnetic particle carriers is removed from the cuvette 320.

[0313] In operation 312, a substrate containing an enzyme 340 is dispensed into the cuvette 320 and then mixed. After a certain reaction time required for the enzyme reaction has elapsed, the cuvette 320 is transported to a photometric system, such as the light measurement device 190.

[0314] In operation 314, the enzyme 340 and immune complex 334 are bound together through a substrate 340 reaction with the enzyme on the labeled antibody 332, and light L is emitted from the immune complex 334 and measured by a photometric system such as light measurement device 190. The light measurement device 190 operates to calculate the amount of antigen contained in the sample according to the amount of light measured.

[0315] Referring to FIG. 5-39, an embodiment of a volumetric detection system 120 is illustrated.

[0316] Figure 5 is a block diagram of an example of the volume detection system 120 of Figure 1. In some embodiments, the volume detection system 120 includes a dispensing tip volume detection device 400 and a container volume detection device 402. The volume detection system 120 further includes a correlation data generation system 404 that generates correlation data 406.

[0317] The dispensing tip volume detection device 400 operates to detect the volume of fluidic material 118 aspirated into the dispensing tip 112 .

[0318] Fluidic substance 118 may be of any type suitable for being dispensed into a container and presented for further analysis. In various embodiments, fluidic substance 118 may be a sample undergoing analysis, a sample preparation component, a diluent, a buffer, a reagent, or any combination of the foregoing. When fluidic substance 118 involves blood or a component thereof, examples of fluidic substance 118 include whole blood, plasma, serum, red blood cells, white blood cells, platelets, a diluent, a reagent, or any combination thereof. Fluidic substance 118 may also 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 substance suspected of containing an analyte of interest. When fluidic substance 118 is a reagent, the reagent may be of various types known for use in analyzing biological samples. 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 particle suspensions. In other embodiments, the reagent can be a chemiluminescent substrate.

[0319] As described herein, the dispensing tip 112 can be of various types and used for different processes. One example of a dispensing tip 112 is a pipetting tip that can be used with a sample pipetting device 152. The dispensing tip volume detection device 400 can utilize the dispensing tip image capture unit 130. An example of a dispensing tip volume detection device 400 is shown and described in further detail with reference to Figures 9-21.

[0320] The vessel volume detection device 402 operates to detect the volume of the fluidic material 118 contained within the vessel 114. As described herein, the vessel 114 can be of various types and used for different processes. Examples of vessels 114 include reaction vessels, sample vessels, and dilution vessels used throughout the processes in the instrument 100. The vessel volume detection device 402 can utilize the vessel image capture unit 132. Examples of the vessel volume detection device 402 are shown and described in further detail with reference to FIGS. 22-39 .

[0321] 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 fluidic material 118 received in the container 110. In some embodiments, the correlation data generation system 404 is a device separate 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.

[0322] 6 is a flowchart illustrating an exemplary method 410 of operating the volumetric detection system 120. In some embodiments, at least some of the operations in the method 410 are performed by the substance preparation system 102, the preparation evaluation system 104, and / or the substance 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 of the operations in the method 410.

[0323] In operation 412, the fluid material 118 is provided into the container 110. In some embodiments, the material preparation system 102 is capable of performing operation 412. In other embodiments, the container 110 is pre-loaded with the fluid material 118 before the container 110 is loaded into and used by the instrument 100.

[0324] In operation 414 , the container 110 containing the fluidic material 118 is transported to an image capture unit, such as the dispensing tip image capture unit 130 and the vessel image capture unit 132 .

[0325] In operation 416, the image capture unit captures an image of the container 110. In some embodiments, the image of the container 110 is a digital image at a predetermined resolution.

[0326] In operation 418, the preparation evaluation system 104 (e.g., the volume detection system 120) analyzes the image to determine the volume of the fluidic material 118 in the container 110. An example of operation 416 is described in further detail with reference to FIG.

[0327] In operation 420, the preparation evaluation system 104 (e.g., the volume detection system 120) determines whether the determined volume falls within a tolerance range. When the determined volume is outside the tolerance range, the provision of the fluidic material 118 into the container 110 is deemed improper. In some embodiments, such a tolerance range is determined based on an allowable deviation from a target volume of the fluidic material 118 intended to be provided into the container 110. When it is determined that the detected volume falls within the tolerance range ("Yes" at operation 420), the method 410 continues with a pre-determined next step. Otherwise ("No" at operation 420), the method 410 proceeds to operation 422.

[0328] In operation 422, the preparation evaluation system 104 (e.g., volume detection system 120) flags the container 110 to indicate that the volume of the fluidic material 118 in the container 110 is not appropriate for subsequent processing. Alternatively, the preparation evaluation system 104 operates to stop the associated testing or analysis process in the instrument 100. In other embodiments, the evaluation results can be used to automatically adjust test results that may be erroneous due to an improper volume of the fluidic material. In yet other embodiments, the evaluation results can be used to automatically adjust the volume of the fluidic material in response to the volume determination, as described herein.

[0329] Figure 7 is a flowchart illustrating an example method 430 for performing operation 418 of Figure 6. Specifically, method 430 provides a process for analyzing captured images of container 110 to determine the volume of fluidic material 118 contained therein.

[0330] In operation 432, the preparation evaluation system 104 (e.g., the volumetric detection system 120) detects a reference point in the image. The reference point is associated with the container 110. In some embodiments, the reference point includes a location or portion of a detectable structure formed on the container 110. In other embodiments, the reference point is configured as part of the container 110. Other examples of reference points are possible. Various image processing methods can be used to detect the surface level of the fluid material 118 in the image.

[0331] In operation 434, the preparation assessment system 104 (e.g., the volume detection system 120) detects the surface level of the fluid material 118 in the container 110 in the image. Various image processing methods can be used to detect the surface level of the fluid material 118 in the image.

[0332] In operation 436, the preparation assessment system 104 (e.g., the volumetric detection system 120) measures the distance between the reference point and the surface level. In some embodiments, the distance is measured by the pixel distance between the reference point and the surface level in the image. In some embodiments, the pixel distance is calculated based on the Euclidean distance between two pixel points.

[0333] In operation 438, the preparation evaluation system 104 (e.g., the volume detection system 120) converts the distance to a volume based on the correlation data 406. The correlation data 406 includes information about the correlation between the volume of the interior of the container 110 and the distance from a reference point to a plurality of different surface levels within the container 110. An exemplary method for generating the correlation data is described with reference to FIG.

[0334] 8 is a flow chart illustrating an exemplary method 450 for operating correlation data generation system 404 to generate correlation data 406. In some embodiments, a portion of instrument 100 is used as correlation data generation system 404. In other embodiments, correlation data generation system 404 generates correlation data independent of instrument 100.

[0335] In operation 452, the correlation data generation system 404 supplies a liquid to a container. The container used in method 450 is the same container 110 that is subjected to the volume detection process herein. The liquid used in method 450 does not need to be the same as the fluidic material 118 used in the instrument 100.

[0336] In operation 454, the correlation data generation system 404 captures an image of the container having the liquid.

[0337] In 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 can be determined similarly to at least some of the operations of method 430, such as operations 432, 434, and 436.

[0338] In operation 458, the correlation data generation system 404 measures the volume of liquid dispensed into the container. Various methods can be used to determine the volume of liquid in the container. Some such methods are described herein.

[0339] In operation 460 , the correlation data generation system 404 correlates the distance calculated in operation 456 and the volume measured in operation 458 .

[0340] At operation 462, the correlation data generation system 404 determines whether a sufficient number of correlations have been performed to generate the correlation data 406. If so (operation 470, "yes"), the method 450 proceeds to operation 464. If not (operation 470, "no"), the method 450 returns to operation 452, where liquid is dispensed into the container, and subsequent operations are performed to determine additional correlations between distance and the volume of liquid in the container. To obtain a sufficient range of correlation data, the amount of liquid dispensed into the container can vary in different cycles of the correlation process. Additionally, the amount of liquid dispensed into the container can remain approximately the same for some of the correlation cycles to obtain reliable results for a particular volume or range of volumes.

[0341] In operation 464, the correlation data generation system 404 creates correlation data 408 based on the multiple correlations performed in operation 460. In some embodiments, the correlation data 408 can be estimated to infer a relationship between distance and volume. For example, a correlation curve, lookup table, or formula can be created from the correlation data 408 to fit the data and estimate a relationship between distance and volume within the container.

[0342] 9-21, an embodiment of the dispensing tip volume detection device 400 of FIG. 5 is described.

[0343] Figure 9 illustrates an example of the dispensing tip volume detection device 400 of Figure 5. In some embodiments, the dispensing tip volume detection device 400 includes a sample aspiration volume detection device 500. Additionally, the dispensing tip volume detection device 400 uses tip volume correlation data 506 generated by a tip volume correlation data generation system 504.

[0344] The sample aspiration volume detection device 500 operates to determine the volume of sample aspirated into the sample pipetting tip of the sample pipetting device 152. An example of the structure and operation of the sample aspiration volume detection device 500 is described below.

[0345] The tip volume correlation data generation system 504 generates tip volume correlation data 506. The tip volume correlation data 506 provides information used by the dispensing tip volume detection device 400 to determine the volume of fluidic material received in a dispensing tip (e.g., a sample pipetting tip). In some embodiments, the tip volume correlation data generation system 504 is a device separate from the dispensing tip volume detection device 400. In other embodiments, the tip volume correlation data generation system 504 is configured to use at least some resources of the dispensing tip volume detection device 400. The tip volume correlation data generation system 504 and the tip volume correlation data 506 are included in, or are examples of, the correlation data generation system 404 and the correlation data 406, as illustrated in FIG. 5 .

[0346] Reliable clinical diagnosis requires accurate and precise aspirating and dispensing of analyzed materials. For example, in automated analyzers that analyze samples such as blood or any other bodily fluid, variations in the dispensed volume of samples and other materials, such as reagents in reaction vessels, relative to the specified volume can affect the analytical results and reduce the reliability of the test and analysis. Therefore, it is beneficial to establish a technique for measuring the aspirated or dispensed volume with high accuracy and selecting only aspirated or dispensed samples whose volume is within a suitable range. One method for measuring liquid volume is to detect the liquid surface level by using a resonant frequency to determine the height of the liquid inside the vessel. In other cases, air pressure is used to determine the viscosity of the liquid (e.g., sample) being aspirated by the dispensing tip. In still other cases, a flow sensor is used to determine the flow rate of the liquid being aspirated or dispensed.

[0347] However, these approaches have various disadvantages. For example, detecting liquid surface levels using resonant frequencies and detecting fluid viscosity using air pressure can determine the volume of liquid in a container, but cannot quantify the volume of liquid aspirated or dispensed. Flow sensors can quantify the volume of liquid passing through the tubing to which the flow sensor is arranged, but cannot reliably measure the volume of liquid aspirated or dispensed. These methods do not have a process for identifying inaccurate sample aspiration in the event of an erroneous result.

[0348] As described in further detail herein, the dispensing tip volume detection device 400 employs image processing methods to quantify the volume of fluidic material (e.g., sample) aspirated. A volume of fluidic material is aspirated into a transparent or translucent container, such as a conical 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 fluidic material to the reference point and correlates the distance to the volume using a volume calibration curve. If the volume aspirated inside the container is not within the aspiration precision or accuracy specifications, the aspiration or the entire test is flagged. A user or operator can receive information about the results of the aspiration.

[0349] 10 schematically illustrates an example structure of a sample aspiration system 510 associated with a sample aspiration volume detection device 500. In the illustrated embodiment, the sample aspiration volume detection device 500 is primarily described and illustrated as an example of a dispensing tip volume detection device 400. However, it will be understood that any type of dispensing tip volume detection device 400 may be used in the same or similar manner as the sample aspiration volume detection device 500.

[0350] In some embodiments, the sample aspiration system 510 includes a sample pipetting module 512 that is movable between different positions along a sample transport guide 514. The sample pipetting module 512 can move to a tip-supply position 516, a sample-dispensing position 518, a tip-disposal position 520, and a sample-aspiration position 522. In some embodiments, the sample pipetting module 512 includes a base 524 and a mandrel 526 supported at the base 524. The sample pipetting 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, also referred to herein as a pipetting tip or probe, an aspiration tip or probe, or a disposable tip or probe 112.

[0351] On the instrument 100, a sample is aspirated by a dispensing tip to avoid the risk of contamination. The sample pipetting module 512 moves to a tip supply position 516, where the base 524 of the module 512 can be vertically lowered to insert a mandrel 526 into a dispensing tip 112 supplied by a dispensing tip supply unit 534. The sample pipetting module 512 then moves to a sample aspiration position 522, where the sample pipetting module 512 operates to aspirate a predetermined volume of sample 540 from a sample container 530. Once the sample is aspirated, the sample aspiration volume detection device 500 detects the volume of sample aspirated into 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 as part of the volume detection process. The sample pipetting module 512 then moves to the sample dispensing position 518 to dispense the aspirated volume of sample into the reaction container 536, and then moves to the tip disposal position 520 to discard the dispensing tip 112 into the dispensing tip disposal unit 538.

[0352] 2. For example, the sample pipetting module 512 corresponds to the sample pipetting device 152 (including the sample aliquot pipetting unit 152A and the sample precision pipetting unit 152B) of the instrument 100. The sample container 530 can correspond to a sample tube. The dispensing tip supply unit 534 can correspond to the pipetting tip feeder 150. The reaction container 536 can correspond to a sample vessel, a reaction vessel, or any other vessel.

[0353] Figures 11, 12A, and 12B illustrate the sample aspiration system 510 of Figure 10. Figure 11 is a perspective view of the sample aspiration system of Figure 10, Figure 12A is a side view of the sample aspiration system 510, and Figure 12B is another side view of the sample aspiration system 510 illustrating the sample pipetting module 512 in a sample aspiration position 522 for volume detection using the sample aspiration volume detection device 500.

[0354] As shown, the dispensing tip image capture unit 130 includes a first camera unit 550 and its associated components mounted on the sample aliquot pipetting unit 152A. In some embodiments, the first camera unit 550 and such other components are configured to move with the corresponding mandrel and dispensing tip of the sample aliquot pipetting unit 152A.

[0355] In some embodiments, the camera unit 550 includes a complementary metal-oxide semiconductor (CMOS) image sensor for capturing color digital images. In other embodiments, the camera unit 550 includes a charge-coupled device (CCD) image sensor for capturing color digital images. As shown in FIG. 12 , the camera unit 550 is located on the side of the dispensing tip 112. Other embodiments of the camera unit 550 are configured to capture black-and-white or grayscale photographs. One example of a camera unit 550 includes a model designated ADVANTAGE 102, available from Cognex Corporation (Natick, MA), such as the AE3-IS Machine Vision Color Camera + IO Board (e.g., part number AE3C-IS-CQBCKFS1-B).

[0356] The dispensing tip image capture unit 130 may further include a light source 552 for the camera 550. The light source 552 is used to illuminate the dispensing tip 112 and its surroundings to be photographed as desired. The light source 552 can be arranged in a variety of locations. In the illustrated embodiment, the light source 552 is positioned behind the dispensing tip 112, opposite the camera unit 550, and is therefore used as a backlight. Other locations for the light source 552 are also possible. One example of a light source 552 includes the MDBL series available from Moritex Corporation (Japan).

[0357] In another embodiment, the camera unit 550 includes a light source 551, such as an LED light, operable to emit light toward the dispensing tip 112. In this configuration, the light source 552 can be replaced by a screen 553 arranged opposite the camera unit 550, such that the dispensing tip 112 is positioned between the camera unit 550 and the screen 553. The screen 553 is used to reflect light back toward the camera unit's field of view (FOV) by reflecting it toward the camera's aperture. The screen 553 can be made of one or more different materials that can provide different reflective intensities. For example, the screen 553 can include a retroreflective sheet, one example of which is 3M 100% reflective sheeting available from 3M Company (Maplewood, MN). TM Scotchlite TM sheet 7610. In other embodiments, light source 552 can be used in conjunction with light source 551 and screen 553 from camera unit 550.

[0358] In some embodiments, the camera unit 550 and light source 552 (or screen 553) are attached to the sample pipetting module 512 and configured to move horizontally with the sample pipetting module 512 so that an image of the dispensing tip 112 can be captured at any position of the sample pipetting module 512. For example, an image of the dispensing tip 112 containing an aspirated sample can be taken at any position after the sample is aspirated (i.e., sample aspiration position 522) and before the sample is dispensed (i.e., sample dispensing position 518). In other embodiments, the camera unit 550 is attached to the sample pipetting module 512, while the light source 552 (or screen 553) is not attached to the sample pipetting module 512. In yet other embodiments, the camera unit 550 is not attached to the sample pipetting module 512, while the light source 552 (or screen 553) is attached to the sample pipetting module 512. In yet other embodiments, neither the camera unit 550 nor the light source 552 (or screen 553 ) is attached to the sample pipetting module 512 .

[0359] Additionally, the dispensing tip image capture unit 130 may include a second camera unit 2550 and its associated components mounted on the sample precision pipetting 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.

[0360] In some embodiments, the second camera unit 2550 and such other components are configured to move with the corresponding mandrel and dispensing tip of the sample aliquot pipetting unit 152A.

[0361] Second camera unit 2550 can be configured similarly to first camera unit 550. One embodiment of camera unit 2550 includes a model designated ADVANTAGE 102, available from Cognex Corporation (Natick, MA), such as the AE3-IS Machine Vision Color Camera + IO Board (e.g., part number AE3-IS-CQBCKFP2-B).

[0362] The dispensing tip image capture unit 130 may further include a light source 2552 for the camera 2550. The light source 2552 is used to illuminate the dispensing tip 112 and its surroundings to be photographed as desired. The light source 2552 can be arranged in a variety of locations. In the illustrated embodiment, the light source 2552 is positioned behind the dispensing tip 112, opposite the camera unit 2550, and is therefore used as a backlight. Other locations for the light source 2552 are also possible. One example of a light source 2552 includes the MDBL series available from Moritex Corporation (Japan).

[0363] In another embodiment, the camera unit 550 includes a light source 2551, such as an LED light, operable to emit light toward the dispensing tip 112. In this configuration, the light source 2552 can be replaced by a screen 2553 arranged opposite the camera unit 550, such that the dispensing tip 112 is positioned between the camera unit 2550 and the screen 2553. The screen 2553 is used to reflect light back toward the field of view (FOV) of the camera unit by reflecting the light toward the camera aperture. The screen 2553 can be made of one or more different materials that can provide different reflective intensities. For example, the screen 2553 can include a retroreflective sheet, one example of which is available from 3M Available from 3M Company (Maplewood, MN) TM Scotchlite TM sheet 7610. In other embodiments, light source 2552 can be used in conjunction with light source 2551 and screen 2553 from camera unit 2550.

[0364] In some embodiments, the camera unit 2550 and light source 2552 (or screen 2553) are configured to be stationary and independent of the movement of the sample pipetting module 512. Other configurations are also possible in other embodiments.

[0365] As described herein, the camera unit 2550 and its associated components can be used for tip alignment detection, as further illustrated in FIG.

[0366] 13 and 14, an embodiment of dispensing tip 112 is described. Specifically, FIG. 13 is a schematic perspective view of an embodiment of dispensing tip 112, and FIG. 14 is a cross-sectional view of the distal end of dispensing tip 112.

[0367] The dispensing tip 112 extends from a proximal end 560 and a distal end 562. The dispensing tip 112 includes a base portion 564 at the proximal end 560 that is configured to attach the dispensing tip 112 to the mandrel 526 of the sample pipetting module 512. The dispensing tip 112 further includes an elongated body portion 566 that extends from the base portion 564. The dispensing tip 112, including the base portion 564 and the body portion 566, defines a pipetting passageway (or channel) 572 for aspirating, containing, and dispensing a fluidic substance. In some embodiments, the dispensing tip 112 (including the dispensing tip 112) is disposable. In other embodiments, the dispensing tip 112 (including the dispensing tip 112) is not disposable or can be used multiple times before being disposed of.

[0368] In some embodiments, the dispensing tip 112 includes a reference line 570 that is detectable by the dispensing tip image capture unit 130. The reference line 570 can 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 level or meniscus of a fluidic material aspirated into the dispensing tip 112 is aligned 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 aspirated fluidic material is aligned above the reference line 570 relative to the distal end 562 (i.e., between the reference line 570 and the proximal end 560).

[0369] The reference line 570 is provided on the dispensing tip 112 in a variety of ways. In some embodiments, the reference line 570 is a detectable structure such as a protrusion, ridge, indentation, notch, or any other visible element formed on the dispensing tip 112. In other embodiments, the reference line 570 is a marker or indicator painted on or attached to the dispensing tip 112. The reference line 570 can be integrally formed or molded into the dispensing tip 112. Alternatively, the reference line 570 is made separately and attached to the dispensing tip 112.

[0370] The reference line 570 is used as a reference point when an image of the dispensing tip 112 is analyzed to determine whether the sample has been properly aspirated for analytical testing. As described herein, the sample aspiration volume detection device 500 measures the aspirated sample volume in the dispensing tip 112 by measuring the distance between the reference line 570 and the sample meniscus. Because the reference line 570 is formed on the dispensing tip 112, the reference line 570 provides a consistent reference point for volume measurement compared to any reference point provided by a structure other than 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 may vary depending on the insertion depth of the dispensing tip 112 into the mandrel 526, thereby causing an inaccurate volume measurement. In contrast, the reference line 570 is stationary relative to the dispensing tip 112 and, therefore, can provide an accurate measurement.

[0371] 14, the pipetting channel 572 includes a tapered section 574, in which the inner diameter becomes smaller from the proximal end 560 to the distal end 562. The pipetting channel 572 further includes a straight section 576, having a constant inner diameter, at or adjacent the distal end 562. The straight section 576 can improve the accuracy and precision of aspirating small volumes, such as about 2-5 μL, while still providing a dispensing tip 112 capable of aspirating larger volumes, such as 250 μL, for aliquotting.

[0372] 15 is a flow chart illustrating an exemplary method 600 of operating the dispensing tip volume detection device 400. In the illustrated example, the method 600 is described primarily with respect to the sample aspiration volume detection device 500. However, the method 600 is also equally applicable to other types of dispensing tip volume detection devices 400. In some embodiments, the method 600 is performed by the sample aspiration system 510 and the sample aspiration volume detection device 500.

[0373] In general, the method 600 uses a metrology algorithm to perform an analysis of the aspirated volume in the dispensing tip and flags the aspiration or test result if the calculated aspirated volume is outside a tolerance range.

[0374] In operation 602, the sample aspiration system 510 operates as programmed to aspirate a fluidic material, such as a sample 540 (FIG. 10), into the dispensing tip 112.

[0375] In operation 604, the sample aspiration system 510 transports the dispensing tip 112 containing the aspirated sample 540 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.

[0376] In 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 at a predetermined resolution.

[0377] In operation 608, the sample aspiration volume detection device 500 analyzes the image to determine the volume of the sample 540 in the dispensing tip 112. An example of operation 608 is described in further detail with reference to Figures 16-19.

[0378] In 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, the aspiration of the sample 540 into the dispensing tip 112 is deemed inappropriate. In some embodiments, such a tolerance range is determined based on an allowable deviation from a target aspiration volume of the sample 540 intended to be aspirated into the dispensing tip 112. The tolerance range may vary depending on the target aspiration volume. Examples of tolerance ranges are as follows:

[0379] [Table 1]

[0380] If it is determined that the detected volume falls within the tolerance range ("Yes" at operation 610), method 600 continues with the pre-determined next step. Otherwise ("No" at operation 610), method 600 proceeds to operation 612.

[0381] In operation 612, the sample aspiration volume detection device 500 flags the aspiration to indicate that the aspirated sample volume in the dispensing tip 112 is not appropriate for subsequent processing. In other embodiments, the entire test result using the aspirated sample can be flagged to indicate or suggest that the test result may be inappropriate. Alternatively, the sample aspiration volume detection device 500 operates to stop the associated testing or analysis process in the instrument 100. In other embodiments, the evaluation result can be used to automatically adjust the test result, which may be erroneous due to an improper volume of fluidic material. In yet other embodiments, the evaluation result can be used to automatically adjust the volume of fluidic material in response to the volume determination, as described herein.

[0382] 16-19, an example of operation 608 of FIG. 15 will be described, in which a captured image is analyzed to determine the sample volume within the dispensing tip. Specifically, FIG. 16 is a flowchart illustrating an exemplary method 630 for performing operation 608 of FIG. 15. Method 630 will also be described with reference to FIGS. 17-19, which illustrate an exemplary analysis of a captured image 620 of a dispensing tip.

[0383] In operation 632, the sample aspiration volume detection device 500 detects the reference line 570 of the dispensing tip 112 in the captured image 620. Various image processing methods can be used to detect the reference line 570 in the image 620. In some embodiments, the reference line 570 is detected by a pattern matching function that searches for a pattern representing a reference line based on pre-trained reference images. For example, such a pattern matching function performs a pattern search that scans the captured image for patterns that are stored in the system and recognized as reference lines. The correlation value or match rate (e.g., % match) can be adjusted. Other methods are also possible in other embodiments. One example of such an image processing method is Cognex Image Processing, which provides various tools such as edge detection ("Edge"), pattern matching ("Pattern Match"), and histogram analysis ("Histogram"). This can be implemented by Cognex In-Sight Vision Software available from Cognex Corporation (Natick, MA).

[0384] In operation 634, the sample aspiration volume detection device 500 detects the center point 650 of the reference line 570. Once the reference line 570 is detected, the center point 650 can be calculated as the midpoint of the reference line 570, as illustrated in FIG.

[0385] In operation 636, the sample aspiration volume detection device 500 detects a surface level 652 ( FIG. 18 ) of the aspirated sample volume in the dispensing tip 112. Various image processing methods can be used to detect the surface level 652 in the image. In some embodiments, similar to operation 632, the surface level 652 is detected by a pattern matching function based on a pre-trained reference image. Other methods are possible in other embodiments.

[0386] In operation 638, the sample aspiration volume detection device 500 detects the center point 654 of the surface level 652. Once the surface level 652 is detected, the center point 654 can be calculated as the midpoint of the line of the surface level 652, as illustrated in FIG.

[0387] In operation 640, the sample aspiration volume detection device 500 measures a distance L1 ( FIG. 19 ) between a center point 650 of the reference line 570 and a center point 654 of the surface level 652. In some embodiments, the distance L1 is measured by the pixel distance between the center points 650 and 654 in the image 620. In some embodiments, the pixel distance is calculated based on the Euclidean distance between the two pixel points.

[0388] In operation 642, the sample aspiration volume detection device 500 converts the distance L1 to a volume based on the 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 point 654 of a plurality of different surface levels 652 within the dispensing tip 112. In some embodiments, the correlation data 506 can be plotted into a correlation curve 660, as illustrated in FIG. 20. An exemplary method of generating the correlation data 506 is described with reference to FIG. 21.

[0389] FIG. 20 is an example correlation curve 660 corresponding to correlation data 506. In some embodiments, correlation curve 660 shows the relationship between distance L1 (e.g., pixel distance) between center points 650 and 654 and volume V1 of sample aspirated in dispensing tip 112. Correlation curve 660 can be obtained by plotting multiple discrete data points included in correlation data 506, as described with reference to FIG. 21. As illustrated in FIG. 20, the correlation curve shows that as distance L1 increases, aspirated volume V1 generally decreases. Because reference line 570 is formed on dispensing tip 112 so as to be aligned above surface level 652, distance L1 generally inversely correlates with volume V1.

[0390] FIG. 21 is a flow chart illustrating an exemplary method 670 for operating the tip volume correlation data generation system 504 to generate the tip volume correlation data 506 .

[0391] In some embodiments, the correlation data 506 is generated using spectroscopic techniques. For example, the tip volume correlation data generating system 504 uses a dye solution to correlate the extracted pixel distance information with the fluid volume information in the dispensing tip. A spectrophotometer can be used to measure the absorbance of the dye at specific wavelengths. In some embodiments, the tip volume correlation data generating system 504 selects multiple points within a target volume range (e.g., 5, 10, 50, 100, and 110 μL), aspirates these volume settings with the dispensing tip, and captures images of the dispensing tip for pixel distance calculation. The tip volume correlation data generating system 504 then plots a calibration curve between the pixel distance calculated from the image and the volume calculated by the spectrophotometer.

[0392] In operation 672, the tip volume correlation data generation system 504 aspirates the dye solution into the dispensing tip 112.

[0393] In operation 674, the tip volume correlation data generation system 504 captures an image of the dispensing tip 112 containing the dye solution.

[0394] In operation 676, the tip volume correlation data generation system 504 extracts the distance between the reference line 570 and the surface line of the dye solution in the image captured in operation 674. In some embodiments, the distance is measured by pixel distance. In some embodiments, the distance is determined similarly to at least some of the operations of method 630, such as operations 632, 634, 636, 638, and 640. Other methods are possible in other embodiments.

[0395] During operations 678, 680, and 682, the tip volume correlation data generation system 504 measures the volume of dye solution aspirated into the dispensing tip 112. Various methods can be used to determine the dye solution volume. In the illustrated example, a spectroscopic approach is used, as described below.

[0396] In operation 678, the tip volume correlation data generation system 504 dispenses the dye solution into a secondary container having a known volume of diluent.

[0397] In operation 680, the tip volume correlation data generation system 504 measures the optical density of the diluted dye solution dispensed into the secondary container. In some embodiments, a spectrophotometer is used to measure the optical density of the dye solution. The spectrophotometer measures the amount of light of a specified wavelength that passes through the diluted dye solution in the secondary container.

[0398] In operation 682, the tip volume correlation data generation system 504 converts the optical density to the volume of the dye solution in the dispensing tip.

[0399] In operation 684 , the tip volume correlation data generation system 504 correlates the distance calculated in operation 676 and the volume calculated in operation 682 .

[0400] In operation 686, the tip volume correlation data generation system 504 determines whether a sufficient number of correlations have been performed to generate the tip volume correlation data 506. If so ("Yes" at operation 686), the method 670 proceeds to operation 688. If not ("No" at operation 686), the method 670 returns to operation 672, where 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 in 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. Additionally, the amount of dye solution aspirated into the dispensing tip can remain substantially the same for some of the correlation cycles to obtain reliable results for a particular volume or range of volumes.

[0401] In operation 688, the tip volume correlation data generation system 504 generates tip volume correlation data 506 based on the multiple correlations performed in operation 684. In some embodiments, the correlation data is illustrated as a correlation curve (e.g., correlation curve 660 in FIG. 20 ) by plotting the pixel distance of each image along with the corresponding aspirated volume measured by the spectrophotometer. The correlation curve is used to estimate the relationship between distance and volume within the dispensing tip 112.

[0402] The dispense tip volume detection device 400 as described with reference to Figures 9-21 can be modified to suit a variety of applications. In some embodiments, the dispense tip volume detection device 400 is used for any fluidic material other than patient samples. In some embodiments, the dispense tip image capture unit of the dispense tip volume detection device 400 does not use a backlight setting. Furthermore, the dispense tip image capture unit can be implemented with a fixed camera and backlight setting, as opposed to a camera and backlight set that moves with the sample pipetting module and other associated devices. The dispense tip reference line can be something other than a line formed on the dispense tip. In some embodiments, the mandrel for the dispense tip is used as a reference point. In some embodiments, the pattern matching function associated with the dispense tip volume detection device 400 employs various algorithms, such as a find line or partition. In some embodiments, the measurement volume range can exceed 110 μL. In some embodiments, the dispense tip volume detection device 400 is used for any container in various shapes (e.g., cylindrical, conical, rectangular, and square) other than the sample pipetting tip as illustrated herein. In other embodiments, the tip volume correlation data generation system 504 employs any liquid other than a dye solution and uses techniques other than spectroscopy. For example, a JIG tip with multiple reference lines corresponding to known volumes can be used.

[0403] One example of the image processing method used above can be implemented by Cognex In-Sight Vision Software available from Cognex Corporation (Natick, MA), which provides a variety of tools such as edge detection ("Edge"), pattern matching ("Pattern Match"), and histogram analysis ("Histogram").

[0404] In some embodiments, the measured volume of the aspirated sample can be used to adjust the relative light units (RLU) of the test result. Because sample volume (as well as substrate / reagent volume, etc.) correlates with RLU for immunoassays, this correlation can be measured and used as a basis for adjustment. Furthermore, the measured volume can be used as feedback to adjust reagent volume for improved ratio agreement and assay performance.

[0405] 22-39, an embodiment of the container volume detection device 402 of FIG. 5 is described.

[0406] Figure 22 illustrates an example of the vessel volume detection device 402 of Figure 5. In some embodiments, the vessel volume detection device 402 includes a reaction vessel dispense volume detection device 700, a reaction vessel residual volume detection device 702, a dispense adjustment device 704, and a reaction vessel detection device 706. The reaction vessel dispense volume detection device 700 uses vessel volume correlation data 712 generated by a vessel volume correlation data generation system 710.

[0407] The reaction vessel dispense volume detection device 700 operates to determine the volume of a fluidic material 118 dispensed into a vessel 114, such as a reaction vessel. An example of the structure and operation of the reaction vessel dispense volume detection device 700 is described and illustrated with reference to Figures 27-31.

[0408] The reaction vessel residual volume detection device 702 operates to determine the volume of fluidic material 118 remaining in a vessel 114, such as a reaction vessel. An example of the reaction vessel residual volume detection device 702 is described and illustrated with reference to Figures 32-34.

[0409] The dispensing adjustment device 704 operates to adjust the operation of a material dispensing device, such as a pipettor and pump device, based on a measurement of a fluidic material volume dispensed into a vessel, such as a reaction vessel 114. An example of the dispensing adjustment device 704 is described and illustrated with reference to Figures 35 and 36.

[0410] The reaction vessel detection device 706 operates to detect the presence or absence of a vessel such as a reaction vessel 114. An embodiment of the reaction vessel detection device 706 is described and illustrated with reference to Figures 37-39.

[0411] The container volume correlation data generation system 710 generates container volume correlation data 712. The container volume correlation data 712 provides information used by the container volume detection device 402 to determine the volume of a fluidic material dispensed into a container (e.g., a reaction vessel). In some embodiments, the container volume correlation data generation system 710 is a separate device from the container volume detection device 402. In other embodiments, the container volume correlation data generation system 710 is configured to use at least some resources of the container volume detection device 402. The container volume correlation data generation system 710 and the container volume correlation data 712 are included in, or are examples of, the correlation data generation system 404 and the correlation data 406, as illustrated in FIG. 5 .

[0412] Before referring to Figures 23-26, it should be noted that reliable clinical diagnostics require accurate and precise aspiration and dispensing of analyzed materials. For example, in automated analyzers analyzing samples such as blood or any other type of bodily fluid, variations in the dispensed or aspirated volume of samples and other materials, such as reagents in a container (e.g., a pipetting tip or reaction vessel) relative to a specified volume can affect the analytical results and reduce the reliability of the test and analysis. Furthermore, in the clinical diagnostic industry, it is difficult to accurately and precisely control and match the volume of fluid dispensed from different pump units. Therefore, it is beneficial to establish a technique for measuring the aspirated or dispensed volume with high accuracy and selecting only aspirated or dispensed samples whose volume is within a suitable range. One method for measuring liquid volume is to monitor the fluid pressure in the fluid line and correlate the fluid pressure to the dispensed volume. In other cases, a flow sensor is used to determine the flow rate of the liquid being aspirated or dispensed. In still other cases, a chemiluminescent signal from the controlled dispensing of IA reagents is used to indicate the presence of excessive residual volume in a container after aspiration from the container. In still other cases, chemiluminescent signals from the controlled dispensing of IA reagents are used to determine the volumetric dispensing characteristics of multiple pump devices.

[0413] However, these approaches have several disadvantages. For example, pressure sensors can determine fluid viscosity but cannot quantify dispensed volume. Flow sensors can quantify the volume of liquid passing through the tubing to which the flow sensors are attached but cannot reliably measure the volume of liquid aspirated or dispensed. Furthermore, due to location offsets, it is difficult to correlate low volume measurements in-line to the exact reaction vessel. Also, chemiluminescent signals cannot detect small residual fluid volumes following aspiration. Chemiluminescent signals do not provide an accurate direct estimate of volume matching characteristics between different pump devices. Chemiluminescent signals confound reagent characteristics and lot variations with system variables of interest, such as dispensed or residual volume.

[0414] As described in further detail herein, the container volume detection device 402 employs image processing methods to quantify the volume of fluidic material dispensed and aspirated into a container (e.g., a reaction vessel). A volume of fluidic material is dispensed or aspirated into a transparent or translucent container, such as a transparent cylindrical vessel. The container is imaged, and a reference point is detected in the image. In some embodiments, a bottom feature of the container is used as the reference point in the image. The container volume detection device measures the distance from the meniscus of the fluidic material to the reference point and correlates the distance to the volume using a volume calibration curve. If the volume dispensed into the container is not within the aspiration accuracy specifications, the entire dispense or test is flagged. A user or operator can receive information about the results of the aspiration.

[0415] In addition, the measured volume of fluid material dispensed into the container is recorded for different combinations of pumps and pipettors in the system and used to calibrate the pump and pipettor combinations and improve the accuracy of controlling different pumps and pipettors in the system.

[0416] Additionally, the container volume detection device 402 can detect the presence of small residual fluid volumes remaining in the container following aspiration. In some embodiments, pattern recognition algorithms are used for such residual volume detection.

[0417] 23-26, an exemplary structure and operation of a container carriage device 720 including a container volume detection device 402 will be described.

[0418] 23 illustrates an exemplary container carriage device 720 that includes the container volume detection device 402. In the illustrated example, the container carriage device 720 is implemented as a cleaning wheel, such as cleaning wheel 176 (FIG. 2), in the instrument 100. Accordingly, the container carriage device 720 is also referred to herein as a cleaning wheel 720. In embodiments, other types of container carriage devices 720 are used in conjunction with the container volume detection device 402.

[0419] As shown, the container carriage device 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 carriage device 720 is configured as a cleaning wheel, such containers 728 include reaction vessels. Accordingly, the containers 728 are also referred to herein as reaction vessels 728.

[0420] In some embodiments, the container volume detection device 402 is mounted to the cleaning wheel 720. As described above, the container volume detection device 402 includes the container image capture unit 132. An exemplary structure of the container image capture unit 132 is described in further detail with reference to Figures 24 and 25.

[0421] 24 and 25, an exemplary structure of the container volume detection device 402 is described, including the container image capture unit 132. Specifically, FIG. 24 is another perspective view of the container carriage device 720 of FIG. 23 illustrating the container image capture unit 132, and FIG. 25 is a top view of the cleaning wheel 720 with the container volume detection device 402, including the container image capture unit 132.

[0422] The container image capture unit 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 photographs. The light source 732 is used to illuminate the container 728, the slot 736, and / or the area surrounding the container 728 and / or slot 736, as desired. The light source 732 can be fixed in various locations. In the illustrated example, the light source 732 is positioned behind the container 728, facing the camera unit 730, and thus is used as a backlight. Other locations for the light source 732 are also possible. One example of the light source 732 includes the MDBL series available from Moritex Corporation (Japan).

[0423] In another embodiment, camera unit 730 includes a light source 731, such as an LED light, operable to emit light toward container 728. In this configuration, light source 732 can be replaced by a screen 733 arranged opposite camera unit 730, such that container 728 is positioned between camera unit 730 and screen 733. Screen 733 is used to reflect light back toward the camera unit's field of view (FOV) by reflecting it toward the camera's aperture. Screen 733 can be made of one or more different materials that can provide different reflective intensities. For example, screen 733 can include retroreflective sheeting, one example of which is 3M 100% reflective sheeting available from 3M Company (Maplewood, MN). TM Scotchlite TMsheet 7610. In other embodiments, light source 732 can be used in conjunction with light source 731 and screen 733 from camera unit 730. One example of camera unit 730 includes a model designated ADVANTAGE 102, available from Cognex Corporation (Natick, MA).

[0424] In some embodiments, the camera unit 730 and the light source 732 (or screen 733) are mounted 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 as the rotatable plate 724 is rotated relative to the housing unit 722, the reaction vessel 728 supported by the rotatable plate 724 is positioned between the camera unit 730 and the light source 732 (or screen 733).

[0425] In some embodiments, the housing unit 722 defines a slot 736 that exposes one of the reaction vessels 728 between the camera unit 730 and the light source 732 (or screen 733). When the reaction vessel 728 is aligned with the camera unit 730 and the light source 732 (or screen 733) through the slot 736 in the housing unit 722, an image of the reaction vessel 728 can be captured by the camera unit 730. In other embodiments in which the housing unit 722 is made of an opaque material, the housing unit 722 includes a transparent or translucent region that replaces the slot 736. The transparent or translucent region allows the camera unit 730 to capture an image therethrough.

[0426] One example of camera unit 730 is an ADV102 Machine Vision Camera, such as part number ADV102-CQBCKFW1-B, available from Cognex Corporation (Natick, MA).

[0427] As described above, patient samples contained in reaction vessels are transported between various modules, units, or devices within the instrument 100. Various aspects of the diagnostic process within the instrument 100 occur within the wash wheel 720. The wash wheel 720 transports multiple reaction vessels 728 around its circumference. The reaction vessels 728 on the wash wheel 720 can accommodate multiple test results. In this configuration, a camera unit 730 and a light source 732 (or screen 733) are fixed to the wash wheel 720. The camera unit 730 faces into the wash wheel 720, where the light source 732 (or screen 733) is located. The camera unit 730 captures images of the reaction vessels 728 as they move 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 vessels 728 are stationary when images of the reaction vessels 728 are captured by the camera unit 730. In other embodiments, camera unit 730 captures images of reaction vessel 728 while it is moving. Images of the reaction vessel can be captured for each reaction vessel 728. Camera unit 730 takes images at multiple steps throughout the diagnostic process as rotatable plate 724 rotates relative to housing unit 722. In some embodiments, reaction vessels can be brought into a location between camera unit 730 and light source 732 (or screen 733) (e.g., container seat 726 located in slot 736) when a diagnostic process is not in progress.

[0428] The wash wheel 720 can operate in different operational modes. In some embodiments, the wash wheel 720 is operated in a test processing mode or a diagnostic routine mode. In other embodiments, the wash wheel 720 can operate in a test preparation mode, such as priming. In the test processing mode, the wash wheel 720 holds one or more containers on a rotatable plate 724 and rotates the containers for a pre-determined analytical test. In the diagnostic routine mode, also referred to herein as automated system diagnostics (ASD), the instrument 100 is idle and does not initiate tests. In some embodiments, in the diagnostic routine mode, the wash wheel 720 is operated to perform at least one of the operations of the preparation evaluation system 104, such as container dispense volume detection (e.g., by the reaction container dispense volume detection device 700), container residual volume detection (e.g., by the reaction container residual volume detection device 702), dispense adjustment (e.g., by the dispense adjustment device 704), and container detection (e.g., by the reaction container detection device 706). In other embodiments, operation of the preparation evaluation system 104 can be performed in an inspection processing mode.

[0429] In some embodiments, the cleaning wheel 720 is operated with multiple dispensing tips, which can have different profiles and accuracies based on their hydraulic properties. In a test processing mode, two or more of the multiple dispensing tips can dispense material into containers on the cleaning wheel 720. In a diagnostic routine mode, the dispensing tips can be operated independently, so that the operating conditions of each dispensing tip can be monitored and evaluated, such as in the dispense adjustments made by the dispense adjustment device 704.

[0430] 26 is a flow chart illustrating an example method 750 of operating the container volume detection device 402 with the cleaning wheel 720. In some embodiments, at least some of the operations in the method 750 are performed by the substance preparation system 102, the preparation evaluation system 104, and / or the substance 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 of the operations in the method 750. In some embodiments, the method 750 includes operations 752, 754, 756, 758, and 760.

[0431] In operation 752, the material preparation system 102 operates to aspirate an excess volume of fluidic material from the reaction vessel 738 on the wash wheel 720. In some embodiments, an excess volume of fluidic material remains in the reaction vessel 738 after one or more pre-determined analytical procedures on the wash wheel 720. Such excess volume of material in the reaction vessel needs to be removed from the reaction vessel 738 for subsequent processing, such as before a substrate is dispensed into the reaction vessel, as illustrated in FIG.

[0432] In operation 754 , the material preparation system 102 transports the reaction vessel 738 to the vessel image capture unit 132 on the cleaning wheel 720 .

[0433] In operation 746, the vessel volume detection device 402 performs residual volume detection in the reaction vessel 738. In some embodiments, the reaction vessel residual volume detection device 702 operates to perform residual volume detection.

[0434] In operation 748 , the material preparation system 102 operates to dispense a fluid material (eg, a substrate as illustrated in FIG. 4) into the reaction vessel 738 .

[0435] In operation 760, the vessel volume detection device 402 performs dispense volume detection in the reaction vessel 738. In some embodiments, the reaction vessel dispense volume detection device 700 operates to perform dispense volume detection.

[0436] 27 is a flow chart illustrating an exemplary method 800 of operating a reaction receptacle dispense volume detection device 700. Although method 800 is described primarily with respect to a reaction receptacle dispense volume detection device 700, method 600 is also equally applicable to other types of receptacle volume detection devices 402. In some embodiments, method 800 is performed by a container carriage device 720 (e.g., a wash wheel) and a reaction receptacle dispense volume detection device 700.

[0437] Generally, the method 800 performs an analysis of the volume of fluidic material dispensed or aspirated into a container and flags the dispense or aspirate result, or test result, if the calculated volume is outside a tolerance range.

[0438] In operation 802, a fluidic material is dispensed as programmed, for example, into a reaction vessel 728 supported in the container carriage device 720. Examples of fluidic materials include a sample, a diluent, a reagent, a substrate, or any combination thereof, as described herein. For example, a diluent or a reagent is used during a diagnostic mode for the cleaning wheel.

[0439] In operation 804, the container carriage device 720 transports the reaction vessel 738 containing the dispensed material to the vessel image capture unit 132. In some embodiments, the vessel image capture unit 132 is arranged to capture an image of the reaction vessel 738 after dispensing without transport. In other embodiments, the dispensing in operation 802 occurs where the vessel image capture unit 132 is arranged in a fixed position and captures an image of the reaction vessel 738 without moving the reaction vessel 738 after dispensing.

[0440] In operation 806, the vessel image capture unit 132 of the reaction vessel dispensing volume detection device 700 captures an image of the reaction vessel 738. In some embodiments, the image of the reaction vessel 738 is a digital image at a predetermined resolution.

[0441] In operation 808, the reaction vessel dispense volume detection device 700 analyzes the image to determine the volume of the fluidic material in the reaction vessel 738. An example of operation 808 is described in further detail with reference to Figures 28 and 29.

[0442] In operation 810, the reaction vessel dispense 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 the fluidic material in the reaction vessel 738 is deemed improper. In some embodiments, such a tolerance range is determined based on an allowable deviation from a target dispense volume of the fluidic material intended to be dispensed into the reaction vessel 738. The tolerance range may vary depending on the target aspiration volume and other factors. As an example, if the target dispense volume (V) is 200 μL, it is deemed acceptable if 194 μL≦V≦206 μL. In other examples, it is deemed acceptable if the standard deviation (V(n)) is equal to or less than ±1 μL.

[0443] If it is determined that the detected volume falls within the tolerance range ("Yes" at operation 810), method 800 continues with the pre-determined next step. Otherwise ("No" at operation 810), method 800 proceeds to operation 812.

[0444] In operation 812, the reaction vessel dispense volume detection device 700 flags the dispense to indicate that the dispensed volume in the reaction vessel 738 is not appropriate for subsequent processing. In other embodiments, the entire test result using the dispensed fluidic material can be flagged to indicate or suggest that the test result may be inappropriate. Alternatively, the reaction vessel dispense volume detection device 700 operates to stop the associated test or analysis process in the instrument 100. In other embodiments, the evaluation results can be used to automatically adjust test results that may be erroneous due to an improper volume of fluidic material (as one example, within a certain volume range, RLU is proportional to substrate volume and, at some point, exceeds the luminometer aperture range, then plateaus and is reduced by a dilution factor). In yet other embodiments, the evaluation results can be used to automatically adjust the volume of the fluidic material in response to the volume determination.

[0445] 28 and 29, an example of operation 808 of FIG. 27 will be described, in which a captured image is analyzed to determine the volume to be dispensed into a reaction vessel. Specifically, FIG. 28 is a flowchart illustrating an exemplary method 830 for performing operation 608 of FIG. 27. Method 830 will also be described with reference to FIG. 29, which illustrates an exemplary analysis of a captured image 780 of a reaction vessel.

[0446] In operation 832, the reaction vessel dispense volume detection device 700 detects a reference portion 784 of the reaction vessel 738 in the captured image 780. In some embodiments, the reference portion 784 includes a bottom portion of the reaction vessel 738. Other portions of the reaction vessel 738 can be used as the reference portion 784.

[0447] Various image processing methods can be used to detect the bottom portion 784 in the image 780. In some embodiments, the bottom portion 784 is detected by a pattern matching function that searches for a pattern representing a bottom portion based on pre-trained reference images. For example, such a pattern matching function performs a pattern search that scans the captured image for patterns that are stored in the system and recognized as bottom portions. The correlation value or match rate (e.g., % match) can be adjusted. Other methods are possible in other embodiments. One example of such an image processing method can be implemented by Cognex In-Sight Vision Software, available from Cognex Corporation (Natick, MA), which provides various tools such as edge detection ("Edge"), pattern matching ("Pattern Match"), and histogram analysis ("Histogram").

[0448] In operation 834, the reaction vessel dispense volume detection device 700 detects the center point 786 of the bottom portion 784. Once the bottom portion 784 is detected, the center point 786 can be calculated as the midpoint of the bottom portion 784, as shown in FIG.

[0449] In operation 836, the reaction vessel dispensing volume detection device 700 detects the surface level 788 ( FIG. 29 ) of the disposed volume in the reaction vessel 738. Various image processing methods can be used to detect the surface level 788 in the image 780. In some embodiments, similar to operation 832, the surface level 788 is detected by a pattern matching function based on a pre-trained reference image. Other methods are possible in other embodiments.

[0450] In operation 838, the reaction vessel dispense volume detection device 700 detects the center point 790 of the surface level 788. Once the surface level 788 is detected, the center point 790 can be calculated as the midpoint of the line of the surface level 788, as illustrated in FIG.

[0451] In operation 840, the reaction vessel dispensing volume detection device 700 measures a distance L2 ( FIG. 29 ) between a center point 786 of the bottom portion 784 and a center point 790 of the surface level 788. In some embodiments, the distance L2 is measured by the pixel distance between the center points 786 and 790 in the image 780. In some embodiments, the pixel distance is calculated based on the Euclidean distance between the two pixel points.

[0452] In operation 842, the reaction vessel dispensing volume detection device 700 converts the distance L2 to a volume based on vessel volume correlation data 712 ( FIG. 22 ). The correlation data 712 includes information about the correlation between the volume within the reaction vessel 738 and the distance L2 between the center point 786 of the bottom portion 784 and the center points 790 of multiple different surface levels 788 within the reaction vessel 738. In some embodiments, the correlation data 712 can be plotted into a correlation curve 860, as illustrated in FIG. 30. An exemplary method of generating the correlation data 712 is described with reference to FIG. 31.

[0453] 30 is an example correlation curve 860 corresponding to correlation data 712. In some embodiments, correlation curve 860 shows a relationship between distance L2 (e.g., pixel distance) between center points 786 and 790 and volume V2 of dispensed fluidic material 782 in reaction vessel 738. In the illustrated example, correlation curve 860 shows a relationship between mass of fluidic material dispensed into reaction vessel 738 and pixel height of the fluidic material in reaction vessel 738. Mass can be converted to volume based on the density of the fluidic material. The pixel height of the fluidic material in the reaction vessel corresponds to distance D2.

[0454] The correlation curve 860 can be obtained by plotting multiple discrete data points included in the correlation data 712, as described with reference to FIG. 31. As illustrated in FIG. 30, the correlation curve shows that as the distance L2 increases, the dispensed volume V2 (or mass M2) generally increases. Because the bottom portion 784 of the reaction vessel 738 is selected as the reference point, the distance L2 generally correlates linearly with the volume V2 (or mass M2). For example, the distance L2 and the volume V2 generally correlate linearly for volumes greater than 10 μL.

[0455] FIG. 31 is a flow chart illustrating an example method 870 for operating the container volume correlation data generation system 710 to generate the container volume correlation data 712.

[0456] In some embodiments, the correlation data 712 is generated using gravimetric analysis. For example, the container volume correlation data generation system 710 uses different volumes of fluid to demonstrate the correlation between the extracted pixel distance information and the fluid volume information in the container. In some embodiments, the container volume correlation data generation system 710 selects multiple points within a target volume range (e.g., 190, 195, 200, 205, and 210 μL), dispenses these volume settings into the container, and takes images of the container for pixel distance calculation. The container volume correlation data generation system 710 then plots a calibration curve between the pixel distance calculated from the image and the mass calculated by gravimetric analysis. The mass is then converted to volume using the density of the fluid.

[0457] In operation 872 , the container volume correlation data generation system 710 measures the mass of an empty container, such as the reaction vessel 738 .

[0458] In operation 874, the container volume correlation data generation system 710 dispenses fluid into the container.

[0459] In operation 876, the container volume correlation data generation system 710 captures an image of the container containing the fluid.

[0460] In operation 878, the vessel volume correlation data generation system 710 extracts the distance between a reference portion of the vessel, such as the bottom portion 784 of the reaction vessel 738, and the surface line of the fluid in the image captured during operation 876. In some embodiments, the distance is measured by pixel distance. In some embodiments, the distance is determined similarly to at least some of the operations of method 830, such as operations 832, 834, 836, 838, and 840. Other methods are possible in other embodiments.

[0461] During operations 880, 882, and 884, the container volume correlation data generation system 710 measures the volume of fluid dispensed into the container. Various methods can be used to determine the fluid volume. In the illustrated example, a gravimetric approach is used, as described below.

[0462] In operation 880, the container volume correlation data generation system 710 measures the mass of the container containing the fluid to be dispensed.

[0463] In operation 882, the container volume correlation data generation system 710 calculates the mass of the fluid contained in the container. In some embodiments, the mass of the fluid in the container can be calculated by subtracting the mass of the empty container (obtained in operation 872) from the total mass of the container containing the fluid (obtained in operation 880).

[0464] In operation 884, the container volume correlation data generation system 710 converts the fluid mass to a volume based on the density of the fluid.

[0465] In operation 886 , the container volume correlation data generation system 710 correlates the distance calculated in operation 878 and the volume obtained in operation 884 .

[0466] In operation 888, the container volume correlation data generation system 710 determines whether a sufficient number of correlations have been performed to generate container volume correlation data 712. If so ("yes" at operation 888), the method 870 proceeds to operation 890. If not ("no" at operation 888), the method 870 returns to operation 874, where another fluid is dispensed into the container, and subsequent operations are performed to determine additional correlations between distance and the volume of fluid in the container. To obtain a sufficient range of correlation data, different amounts of fluid are dispensed into the container in different correlation cycles. Additionally, the amount of fluid dispensed into the container can remain substantially the same for some of the correlation cycles to obtain reliable results of the correlation.

[0467] In operation 890, the container volume correlation data generation system 710 generates container volume correlation data 712 based on the multiple correlations performed in operation 886. In some embodiments, the correlation data 712 is illustrated as a correlation curve (e.g., correlation curve 860 in FIG. 30 ) by plotting the pixel distance of each image along with the corresponding dispensed volume. The correlation curve is used to estimate the relationship between distance and volume within the container.

[0468] 32-34, an exemplary operation of the reaction vessel residual volume detection device 702 will be described.

[0469] 32 is a flow chart illustrating an example method 900 of operating the reaction vessel residual volume detection device 702. In some embodiments, the method 900 includes operations 902, 904, 906, 908, 910, and 912.

[0470] Generally, method 900 analyzes the container to determine if it contains a residual volume after it is aspirated. If the container contains a volume that is outside the tolerance range, the aspiration or inspection result is flagged.

[0471] In operation 902 , the reaction vessel residual volume detection device 702 aspirates a substance from a vessel, such as the reaction vessel 738 .

[0472] In operation 904, the reaction receptacle residual volume detection device 702 transports the receptacle to the receptacle image capture unit 132. In some embodiments, the receptacle image capture unit 132 is arranged to capture an image of the receptacle after aspiration without transport. In other embodiments, the aspiration in operation 902 occurs where the receptacle image capture unit 132 is arranged in a fixed position and captures an image of the receptacle without moving the receptacle after aspiration.

[0473] In operation 906, the container image capture unit 132 captures an image of the container. In some embodiments, the image of the container is a digital image at a predetermined resolution.

[0474] In operation 908, the reaction vessel residual volume detection device 702 analyzes the image to determine the presence of a substance in the vessel. An example of operation 908 is described in further detail with respect to FIGS.

[0475] In operation 910, the reaction vessel residual volume detection device 702 determines whether the presence of residual volume falls within a tolerance range. When the presence of residual volume falls outside the tolerance range, aspiration of material from the vessel is deemed inappropriate. The tolerance range represents the range of residual volumes in the reaction vessel that are tolerable for acceptable test results. For example, the reaction vessel does not need to be aspirated completely empty for an acceptable test result. In some embodiments, such a tolerance range is determined in terms of a pattern match score between the captured image and pre-trained images, as further described in FIG. 33 . As an example, if a residual volume of 4 μL or less in a reaction vessel is deemed acceptable, a pattern match score that can be interpreted as similar to an image of a reaction vessel containing a volume of 4 μL would be used as the tolerance threshold.

[0476] If it is determined that the presence of residual volume falls within the tolerance range ("Yes" at operation 910), method 900 continues with the pre-determined next step. Otherwise ("No" at operation 910), method 900 proceeds to operation 812.

[0477] In operation 912, the reaction vessel residual volume detection device 702 flags the aspiration result to indicate that the aspiration from the vessel is not appropriate for subsequent processing. In other embodiments, the entire test result using the aspirated vessel can be flagged to indicate or suggest that the test result may be inappropriate. Alternatively, the reaction vessel residual volume detection device 702 operates to stop the associated testing or analysis process in the instrument 100. In other embodiments, the evaluation result can be used to automatically adjust test results that may be erroneous due to an inappropriate volume of fluidic material.

[0478] 33 and 34, an example of operation 908 of FIG. 32 will be described, in which a captured image is analyzed to determine residue 952 within a container. Specifically, FIG. 33 is a flowchart illustrating an example method 930 for performing operation 908 of FIG. 32. Method 930 will also be described with reference to FIG. 34, which illustrates an example analysis of a captured image 942 of a container.

[0479] In operation 932, the reaction vessel residual volume detection device 702 detects an area of interest 946 in the captured image 942. In some embodiments, the area of interest 946 includes a bottom portion of the vessel 944. In some embodiments, the vessel 944 in the image represents the reaction vessel 738 discussed above. Another portion of the reaction vessel 738 can be used as the reference portion 784.

[0480] Various image processing methods can be used to detect the bottom portion 946 in the image 942. In some embodiments, the bottom portion 946 is detected by a pattern matching function that searches for a pattern representing a bottom portion based on pre-trained reference images. For example, such a pattern matching function performs a pattern search that scans the captured image for patterns that are stored in the system and recognized as bottom portions. The correlation value or match rate (e.g., % match) can be adjusted. Other methods are possible in other embodiments. One example of such an image processing method can be implemented by Cognex In-Sight Vision Software, available from Cognex Corporation (Natick, MA), which provides various tools such as edge detection ("Edge"), pattern matching ("Pattern Match"), and histogram analysis ("Histogram").

[0481] In operation 934, the reaction vessel residual volume detection device 702 compares the area of interest 946 to a reference image 948. In some embodiments, the reference image 948 includes a portion 950 that corresponds to the area of interest 946. In other embodiments, the reference image 948 is only a portion 950 of the captured image 942 that corresponds to the area of interest 946.

[0482] In some embodiments, the reference image 948 represents an image of the same empty container 944. A pre-trained image of the empty container 944 is used as the reference image 948 because ideal suction leaves no residual fluid in the bottom portion of the container 944. In other embodiments, other images can be used as the reference image 948.

[0483] In operation 936, the reaction vessel residual volume detection device 702 generates a match score between the captured image 942 and the reference image 948. The match score represents how closely the captured image 942 matches the reference image 948. The match score is used as a metric to determine a cutoff for the presence of excess residual fluid in the vessel.

[0484] At operation 938, the reaction vessel residual volume detection device 702 determines whether the match score meets the threshold. If the match score meets the threshold ("Yes" at operation 938), it is considered that there is no residual fluid or acceptable residual fluid in the vessel, and method 930 proceeds to a pre-determined next step. Otherwise ("No" at operation 938), method 930 continues at operation 940. For example, if the match score is below a pre-determined threshold or cutoff value, it is considered that there is excessive residual fluid in the vessel, and method 930 proceeds to operation 940.

[0485] In operation 940, the reaction vessel residual volume detection device 702 flags the aspiration result to indicate that the aspiration from the vessel is not appropriate for subsequent processing. In other embodiments, the entire test result using the aspirated vessel can be flagged to indicate or suggest that the test result may be inappropriate. Alternatively, the reaction vessel residual volume detection device 702 operates to stop the associated testing or analysis process in the instrument 100. In other embodiments, the evaluation result can be used to automatically adjust test results that may be erroneous due to an inappropriate volume of fluidic material.

[0486] Alternatively, method 930 uses other approaches to perform image comparisons and assign cutoff values. Examples of such approaches utilize common classification tools such as logistic regression, support vector machines, neural networks, convolutional neural networks, and classification trees.

[0487] 35 and 36, an exemplary operation of dispense regulation device 704 will be described.

[0488] FIG. 35 is a block diagram of an exemplary system 960 in which the dispense adjusting device 704 is operated.

[0489] In general, the dispense adjusting device 704 can use the volumetric measurement capabilities of the vessel image capture unit 132 to make built-in adjustments to the pipettors and pumps, thereby improving pipetting accuracy and overall system precision. In the illustrated example, single- or multiple-volume dispenses are made into vessels and then transferred to a wash wheel for measurement. The results of volumetric measurements, which may be made by the reaction vessel dispense volume detection device 700 as described above, are obtained, and the dispense adjusting device 704 determines the accuracy for each pump and pipettor combination. In some embodiments, the measured volume associated with the pump is used to adjust the operating parameters of the pump and pipettor combination. As an example, the step resolution for each pump can be adjusted, or an offset can be added to the software instructions for each pump. After adjustments, the dispense adjusting device 704 can check the pumps again for accuracy and readjust the pumps if necessary. In some embodiments, the dispense adjusting device 704 performs such adjustments while the instrument is idle for a clinical test. In other embodiments, the dispense adjusting device 704 performs adjustments during instrument initialization. In some embodiments, the dispensing adjustment device 704 periodically makes adjustments and monitors trends in pump performance so that a user or repair department can remotely monitor the status and make maintenance decisions, such as when to send a repair technician for maintenance or part replacement.

[0490] 35, the substance preparation system 102 dispenses a fluidic substance 118 into one or more containers 114 (e.g., reaction containers 728 on a wash wheel). The reaction container dispense volume detection device 700 then performs a volume measurement in the container 114 as described herein and provides the result of the volume measurement 962 to the dispense adjusting device 704. In some embodiments, the dispense adjusting device 704 analyzes the result of the volume measurement 962 and then generates calibration information 964, which can be used to calibrate the substance preparation system 102 to improve dispense accuracy.

[0491] 36 is a flow chart illustrating an example method 970 for operating the dispense adjustment device 704. In some embodiments, the method 970 includes operations 972, 974, 976, 978, 980, and 982.

[0492] In operation 972, the dispensing adjustment device 704 receives one or more operating parameters of the substance preparation system 102. As described above, the substance preparation system 102 includes one or more substance dispensing devices, such as the sample pipetting device 152, the reagent pipetting device, and the substrate pipetting device 178, that operate to dispense fluidic substances 118 into the containers 114. The operating parameters include various information about the configuration, settings, and operational status of the substance dispensing devices. In some embodiments, such substance dispensing devices include pump devices that operate the dispensing units (e.g., pipetters). Some examples of pump devices are operated by various types of motors, such as stepper motors. When a stepper motor is used, the operating parameters can include a step resolution that is controlled to adjust the amount of dispensing through the pipettor.

[0493] In operation 974, the dispense adjustment device 704 receives a target dispense volume of the fluidic material 118. The target dispense volume represents the volume of the fluidic material 118 that is intended to be dispensed into the container 114 based on the operating parameters of the material dispensing device.

[0494] In operation 976 , the dispense adjustment device 704 receives the detected volume that has been dispensed into the container 114 .

[0495] In operation 978, the dispensing adjustment device 704 compares the detected volume with the target volume. As an example, a first material dispensing device including a first pump device using a first pipettor is configured to dispense a target volume of 100 μL into a container. After dispensing, the volume dispensed into the container is detected to be 99.9 μL. The dispensing adjustment device 704 then compares the target volume of 100 μL and the detected volume of 99.9 μL and determines that there is a 0.1 μL difference between the target volume and the detected volume in the first material dispensing device.

[0496] In some embodiments, multiple dispense instances from a single material dispensing device are considered a group. As an example, a particular material dispensing device performs a first dispense, a second dispense, and a third dispense using a pump device and a container (or three containers) with a target volume of 100 μL. After the three dispense instances, the volume dispensed into the container is detected to be 100.5 μL in the first dispense instance, 99.5 μL in the second dispense instance, and 100 μL in the third dispense instance. In some embodiments, all of the detected volumes can be used together to calibrate the material 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 material dispensing device, for example, by adjusting the step resolution of its stepper motor. 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 material dispensing device for each dispense instance.

[0497] In other embodiments, multiple dispensing instances from multiple material dispensing devices are considered a group. As an example, with a target volume of 100 μL, a first material dispensing device performs a first dispense, a second material dispensing device performs a second dispense, and a third material dispensing device performs a third dispense. After dispensing, the volume dispensed by the first material dispensing device is detected to be 100.5 μL, the volume dispensed by the second material dispensing device is detected to be 99.5 μL, and the volume dispensed by the third material dispensing device is detected to be 100 μL. In some embodiments, all of the detected volumes can be used together to calibrate the material 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 material dispensing device, for example, by adjusting the step resolution of its stepper motor. In this example, calibration information 964 is generated and used to reduce the standard deviation. In other embodiments, the detected volume can be used to calibrate individual material dispensing devices, as described above.

[0498] In operation 980, the dispensing adjustment device 704 generates calibration information 964 for the substance dispensing device. The calibration information 964 includes information for controlling the substance dispensing device so that the volume dispensed by the substance dispensing device is varied to more closely match the target volume. If the substance dispensing device includes a stepper motor, the calibration information 964 includes adjusting the step resolution of the stepper motor to adjust the volume dispensed by the stepper motor.

[0499] In operation 982, the dispensing adjustment device 704 adjusts the operating parameters of the substance dispensing device based on the calibration information 964. The substance dispensing device can operate to dispense the same or different volumes based on the modified operating parameters. In the example above, where three dispense instances are considered a group, the volume dispensed into the container after calibration is again detected.

[0500] 37-39, an exemplary operation of the reaction vessel detection device 706 will be described.

[0501] 37 is a flow chart illustrating an exemplary method 1000 of operating the reaction vessel detection device 706. In some embodiments, the method 1000 includes operations 1002, 1004, 1006, 1008, 1010, and 1012.

[0502] Typically, during system initialization or reset, containers inside the cleaning wheel must be removed. The reaction container detection device 706 can utilize the container image capture unit 132 to determine whether all or some of the containers have been removed during this initialization sequence. In some embodiments, the cleaning wheel operates to send to all positions, with each container location being checked by the image capture unit. At each cleaning wheel send position, the reaction container detection device 706 can perform image processing, such as a pattern matching algorithm, to check for the presence of a container by comparing the captured image to a reference image (e.g., an image of the cleaning wheel without a container). The reaction container detection device 706, according to exemplary embodiments of the present disclosure, provides reliable results in contrast to other approaches that examine or utilize the volume within a container. If the reaction container detection device 706 looks for a close match to the geometric shape of the container, a large deviation from the reference image would indicate the presence of a container, and a small deviation would indicate the absence of a container. If a presence is determined, the system can remove the container and check again to confirm that the container was successfully removed. Once it is determined that no containers are present at a given wheel location, the wheel can be dispatched to the next location and the process repeated.

[0503] In the illustrated example, the reaction vessel detection device 706 is described primarily with respect to the cleaning wheel 720. However, in other embodiments, the reaction vessel detection device 706 is used with other types of container carriage devices.

[0504] In operation 1002 , the reaction vessel detection device 706 uses the vessel image capture unit 132 to capture an image of a vessel slot 1044 ( FIG. 39 ) (eg, slot 736 ) on the cleaning wheel 720 .

[0505] In operation 1004, the reaction vessel detection device 706 analyzes the image to determine the presence or absence of a vessel 1042 ( FIG. 39 ) (e.g., reaction vessel 738) on the cleaning wheel 720. An example of operation 1004 is described in further detail with reference to FIGS. 38 and 39 .

[0506] At operation 1006, the reaction vessel detection device 706 determines whether a vessel is present in the vessel slot. If so (operation 1006, "yes"), the method 1000 continues at operation 1008. Otherwise (operation 1006, "no"), the method 1000 proceeds to operation 1010.

[0507] In operation 1008, the reaction vessel detection device 706 removes the vessel from the vessel slot of the cleaning wheel 720. In other embodiments, another device in the instrument 100 (such as a transport or carriage device as illustrated in FIG. 2) operates to remove the vessel from the cleaning wheel 720. In yet other embodiments, the vessel is manually removed from the cleaning wheel 720.

[0508] In operation 1010, the reaction vessel detection device 706 determines whether all of the positions of the wash wheel 720 have been analyzed through previous operations (e.g., operations 1002, 1004, 1006, and 1008). If so (operation 1010, "yes"), the method 1000 proceeds with the pre-determined next step. Otherwise (operation 1010, "no"), the method 1000 proceeds to operation 1012.

[0509] In operation 1012, the reaction vessel detection device 706 moves the wash wheel 720 to the next position and repeats operation 1002 and subsequent operations.

[0510] 38 and 39, an example of operation 1004 of FIG. 37 will be described, in which a captured image is analyzed to determine the presence of a container on the cleaning wheel. Specifically, FIG. 38 is a flowchart illustrating an example method 1020 for performing operation 1004 of FIG. 37. Method 1020 will also be described with reference to FIG. 39, which illustrates an example analysis of a captured image 1040 of a container slot 1044 on the cleaning wheel.

[0511] In operation 1022, the reaction vessel detection device 706 detects an area of interest 1046 in the captured image 1040. In some embodiments, the area of interest 1046 includes at least a portion of a vessel slot 1044 (e.g., slot 736) of the cleaning wheel 720. In some embodiments, the area of interest 1046 includes a bottom portion of the vessel or a portion in the image corresponding to the location of the bottom portion of the vessel. One exemplary method for detecting the area of interest can be implemented by Cognex In-Sight Vision Software available from Cognex Corporation (Natick, MA), which provides a variety of tools such as edge detection (“Edge”), pattern matching (“Pattern Match”), and histogram analysis (“Histogram”).

[0512] In operation 1024, the reaction vessel detection device 706 compares the area of interest 1046 to the reference image 1048. In some embodiments, the reference image 1048 includes a portion that corresponds to the area of interest 1046. In other embodiments, the reference image 1048 itself corresponds to the area of interest 1046 in the captured image 1040.

[0513] In some embodiments, the reference image 1048 represents an image of the container slot 1044 without a container 1042 therein (FIG. 39). In other embodiments, other images can be used as the reference image 948. For example, the reference image is an image of the container slot with a container therein.

[0514] In operation 1026, the reaction vessel detection device 706 generates a match score between the captured image 1040 and the reference image 1048. The match score represents how closely the captured image 1040 matches the reference image 1048. The match score is used as a metric to determine a cutoff for the presence of a vessel 1042 in a slot 1044 of the cleaning wheel 720.

[0515] In operation 1028, the reaction vessel detection device 706 determines whether the match score meets the threshold. If the match score meets the threshold ("yes" at operation 1028), a vessel is considered not present in the cleaning wheel slot, and method 1020 proceeds to operation 1030. Otherwise ("no" at operation 1028), a vessel is considered present in the cleaning wheel slot, and method 1020 continues at operation 1032. For example, if the match score is below a predetermined threshold or cutoff value, a vessel is considered present in the cleaning wheel slot, and method 1020 proceeds to operation 1032.

[0516] In operation 1030 , the reaction vessel detection device 706 verifies the absence of a vessel 1042 in the slot 1044 of the cleaning wheel 720 .

[0517] In operation 1032 , the reaction vessel detection device 706 verifies the presence of a vessel 1042 in a slot 1044 of the cleaning wheel 720 .

[0518] As described with reference to FIGS. 22-39 , the container volume detection device 402 can be modified to suit a variety of applications. For example, the container volume detection device 402 can be applied to any analyzer that prepares and / or uses fluidic materials to detect an analyte of interest, such as an in vitro diagnostic (IVD) analyzer. 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 a total reaction volume check. 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 yet other embodiments, the calibration curve used in the container volume detection device 402 is established using a JIG reaction vessel with lines at known volume heights on the outer wall. For residual volume detection in the container volume detection device 402 (eg, for volumes greater than 10 μL), line finding or grayscale matching may be applicable.

[0519] The container volume detection device 402, according to exemplary embodiments of the present disclosure, can be used in a variety of other applications. In some embodiments, the container volume detection device 402 is used to detect dispense tip misalignment. For example, the container image capture unit 132 is used to determine whether the dispense tip is off-center as 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 cleaning wheel is tilted or mispositioned. In yet other embodiments, the container volume detection device 402 is used to detect any abnormal conditions, such as splashing, foaming, or poor magnetization. In yet other embodiments, the container volume detection device 402 is used to detect RV integrity, such as scratches, discoloration, and transparency. In yet other embodiments, the container volume detection device 402 is used to detect tip alignment integrity.

[0520] The light source used in the container volume detection device 402 need not be located behind the reaction container. Other locations for the backlight device are possible. Alternatively, the light source can be integrated into the 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 container, as illustrated herein. In some embodiments, the camera unit used in the container volume detection device 402 is configured to monitor the temperature of the container and / or the wash wheel using the IR spectrum.

[0521] As described above, the reaction vessel detection device 706 of the vessel volume detection device 402 can be applied to any container carriage device other than a wash wheel. As described above, the dispensing adjustment device 704 of the vessel volume detection device 402 can operate to measure the level of the substrate volume and use the measured level to adjust the RLU of the test result and fine-tune the calibration to improve accuracy.

[0522] According to exemplary embodiments of the present disclosure, instrument 100 employs various programming solutions to implement image evaluation operations such as pattern matching as described herein. In some embodiments, such programming solutions are developed using off-the-shelf software solutions. One example of a programming solution is In-Sight Explorer Software (also referred to as In-Sight Vision Software) available from Cognex Corporation (Natick, MA).

[0523] Referring now to FIG. 40 and subsequent figures, an embodiment of a dispense tip evaluation system 122 is described.

[0524] Figure 40 is a block diagram of an example of the dispense tip evaluation system 122 of Figure 1. In some embodiments, the dispense tip evaluation system 122 includes a dispense tip integrity evaluation device 1100.

[0525] The dispensing tip integrity assessment device 1100 operates to assess the quality of the fluidic material 118 aspirated into the dispensing tip 112 and the integrity of the dispensing tip 112. As described herein, the dispensing tip 112 can be of various types and used for different processes. One example of a dispensing tip 112 is a pipetting tip that can be used with a sample pipetting device 152. The dispensing tip integrity assessment device 1100 can utilize a dispensing tip image capture unit 130. An example of a dispensing tip integrity assessment device 1100 is shown and described in further detail with reference to FIG. 41 .

[0526] Figure 41 is a block diagram of an example implementation of the dispensing tip integrity assessment device 1100 of Figure 40. In some embodiments, the dispensing tip integrity assessment device 1100 includes a sample quality detection device 1112 and a tip alignment detection device 1114.

[0527] In some embodiments, the dispensing tip integrity assessment device 1100 is implemented in conjunction with the sample aspiration system 510 of Figure 10. In other embodiments, the dispensing tip integrity assessment device 1100 can be used in other types of systems operable to aspirate or dispense fluidic materials using a container.

[0528] The sample quality detection device 1112 operates to detect the quality of the sample aspirated into the sample pipetting tip of the sample pipetting device 152. Examples of the structure and operation of the sample quality detection device 1112 are described with reference to Figures 42-55.

[0529] In addition to detecting the quality of the sample in the dispensing tip, the sample quality detection device 1112 can also be used to detect the quality of the fluidic material 118 contained in the container 114. As described herein, the container 114 can be of various types and used for different processes. Examples of containers 114 include reaction vessels, sample vessels, and dilution vessels used throughout the processes in the instrument 100. In some embodiments, the sample quality detection device 1112 can utilize a container image capture unit 132.

[0530] The tip alignment detection device 1114 operates to detect tolerances and misalignment of the dispensing tip 112 relative to the sample pipetting module 512 and / or the dispensing tip image capture unit 130. Allowable tolerances of the dispensing tip 112 and / or misalignment of the dispensing tip 112 can reduce the accuracy of detecting the aspirated sample volume in the dispensing tip 112, for example, as performed by the dispensing tip volume detection device 400 herein. The tip alignment detection device 1114 further operates to adjust or correct the detected volume of liquid aspirated into the dispensing tip 112 based on the detection of the tolerances and misalignment. Examples of the structure and operation of the tip alignment detection device 1114 are described with reference to Figures 56-68.

[0531] 42-55, an embodiment of a sample quality detection device 1112 is described.

[0532] 42 illustrates an example of a sample quality detection device 1112. In some embodiments, the sample quality detection 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 is an aspirated sample 1130, an image 1132, one or more color parameters 1134, classification data 1136, and a sample classification result 1138.

[0533] The sample quality detection device 1112 operates to evaluate the quality of a sample aspirated using the dispensing tip and determine whether the sample is of sufficient quality for subsequent analysis. If sample quality is determined to be compromised, the instrument can inform the user about the sample quality and / or stop testing.

[0534] In some embodiments, the sample provided in the sample tube (e.g., sample 324 in FIG. 4 ) contains various interfering substances or substances that can compromise sample integrity and affect clinical testing. Such samples containing more than acceptable levels of interfering substances can cause erroneous but believable results that cannot be easily detected. For chemical and immunoassay systems, examples of interfering substances include hemoglobin, bilirubin (also referred to herein as jaundice, a condition caused by bilirubin), and lipids (also referred to herein as lipemia, a condition caused by lipids). Depending on the assay, the concentrations of hemoglobin, jaundice, and lipemia should be limited to predetermined levels to ensure that no interference occurs that would distort results.

[0535] Various methods have been used to assess sample quality. Some examples of such methods include chemical analyzers that use spectrophotometers. Using such spectrophotometers to determine sample quality is an independent event from the chemical analysis of the sample and, therefore, depending on the manufacturer, may require additional samples to determine sample integrity. Because spectrophotometers use specific wavelengths for measurement, the systems require either LED or collimated light sources and use complex mathematical processing due to the spectral overlap of interferents with the end product of some assays. Also, hyperlipidemic samples often exhibit volumetric displacement, which can affect the sample volume in testing. Therefore, methods for assessing sample quality require separate testing to do so, incurring additional costs. As a result, primary sample testing can be performed only after a quality check, resulting in delays to primary sample testing. Alternatively, if primary sample testing and sample quality testing are performed simultaneously, a compromised sample can be flagged only during or after primary sample testing. In this case, the sample must be redrawn, again causing a delay in test results.

[0536] In contrast, the sample integrity detection device 1112 uses various components of the instrument 100 that are integrated with and configured for analysis of a sample. Thus, a single instrument can both assess the quality of a sample and perform analysis of the sample without incurring delays and additional costs.

[0537] As described above, in some embodiments, the sample integrity detection device 1112 is used in conjunction with the sample aspiration system 510 of Figure 10. In other embodiments, the sample integrity detection device 1112 can be used in other types of systems operable to aspirate fluidic materials using a container.

[0538] In the illustrated example, the sample integrity detection device 1112 is described primarily in the context of an immunoassay analyzer, as illustrated in Figures 2 and 4. For example, the sample integrity detection device 1112 operates to detect the concentration of interferents, such as hemoglobin, icterus, and lipemia, in a sample aspirated into a dispensing tip. However, in other embodiments, the sample integrity detection device 1112 is used to assess the quality of a sample in other types of instruments.

[0539] Generally, the sample integrity detection device 1112 acquires an image of a transparent, cylindrically shaped container with fluid inside. The sample integrity detection device 1112 then extracts information about individual pixels within a region of interest in the image. The information about the pixels is used to classify the fluid. The sample integrity detection device 1112 includes a classifier model that employs classifiers used to group fluids into categories. If the color of the fluid aspirated into the container is not within pre-determined specifications, the aspiration or test is flagged. In some embodiments, the instrument operator receives information about the fluid aspiration when the fluid integrity is determined to be out of specification for a given fluid.

[0540] Still referring to FIG. 42 , image capture device 1120 operates to capture image 1132 of sample 1130 being aspirated with dispensing tip 1180 ( FIG. 45 ). In some embodiments, sample 1130 is an example of sample 540, and dispensing tip 1180 is an example of dispensing tip 112, as shown in FIG. 10 . In some embodiments, image capture device 1120 operates to capture more than one image of sample 1130 being aspirated with dispensing tip 1180 at varying time intervals. For example, image capture device 1120 operates to sequentially capture two images of sample 1130 being aspirated with dispensing tip 1180, approximately 30 milliseconds apart, or any other time interval. In some embodiments, image capture device 1120 utilizes dispensing tip image capture unit 130, which includes camera unit 550 and light source 552. In some embodiments, light source 552 of image capture device 1120 generates white backlight. In other embodiments, the light source 552 provides one or more colored backlights that can be either fixed or variable during image capture. In some embodiments, the light source 552 can generate backlights with different exposure times. For example, the light source 552 can generate backlights with an exposure time of approximately 6 milliseconds, and the image capture device 1120 operates to capture a first image immediately after the exposure time of approximately 6 milliseconds and a second image at approximately 30 seconds. In one embodiment, the first image is acquired approximately 0.2 seconds after the reagent is dispensed into the container. In an embodiment, the second image is acquired approximately 6.5 seconds after mixing. In a further embodiment, the first image is acquired approximately 0.2 seconds after the reagent is dispensed into the container, and the second image is acquired approximately 6.5 seconds after mixing. Varying exposure times can improve evaluation of the captured images for color parameters. For example, if the sample has a high density, a longer exposure time will similarly result in a brighter image so that the image evaluation device 1122 can effectively evaluate different color parameters.

[0541] The image evaluation device 1122 operates to process and evaluate the captured image 1132 to generate one or more color parameters 1134. The color parameters 1134 are used to determine the concentration levels of interferents contained in the sample 1130. Examples of the image evaluation device 1122 are shown and described in further detail with reference to Figures 44-48.

[0542] The classification data generation device 1124 operates to generate classification data 1136. As described below, the classification data 1136 includes a list of classification labels for different amounts of interferents that are used by the classification device 1126 to generate sample classification results 1138. Examples of the classification data generation device 1124 are shown and described in further detail with reference to Figures 49-53.

[0543] The classification device 1126 operates to generate a sample classification result 1138 based on the color parameters 1134 and the classification data 1136. The sample classification result 1138 includes information indicative of the quality of the sample 1130. For example, the sample classification result 1138 includes information representing the concentration levels of interferents, such as hemoglobin, icterus, and lipemia, in the aspirated sample 1130, indicating that the concentration levels of the interferents, either individually or in combination, are acceptable. Thus, the sample classification result 1138 is used to determine whether the sample 1130 is of sufficient quality for laboratory analysis in the instrument 100. Examples of the classification device 1126 are shown and described in further detail with reference to FIGS. 54-55 .

[0544] 43 is a flow chart illustrating an exemplary method 1150 for operating the sample integrity detection device 1112. In some embodiments, the method 600 is performed by the sample aspiration system 510 (FIG. 10) and the sample integrity detection device 1112.

[0545] Generally, method 1150 analyzes the quality of the sample in the dispensing tip in terms of the concentration of interfering substances such as hemoglobin, icterus (bilirubin), and lipemia, and flags the test results if the assessed quality is classified outside of the acceptable range.

[0546] In operation 1152, the sample aspiration system 510 operates as programmed to aspirate a fluidic material such as sample 1130 into the dispensing tip 1180 (Figure 45) (which is an example of the dispensing tip 112 as shown in Figure 10).

[0547] In operation 1154, the sample aspiration system 510 transports the dispensing tip 1180 containing the aspirated sample 1130 to the image capture device 1120 (including the 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.

[0548] In operation 1156, the dispensing tip image capture unit 130 captures an image 1132 of the dispensing tip 1180. In some embodiments, the image 1132 of the dispensing tip 1180 is a digital image at a predetermined resolution. In some embodiments, the dispensing tip image capture unit 132 can capture more than one image of the dispensing tip 1180 at varying time intervals. For example, the dispensing tip image capture unit 132 can capture two images of the dispensing tip 1180 about 30 milliseconds apart, or any other time interval. In operation 1158, the sample integrity detection device 1112 analyzes the image 1132 to determine the level of interferents in the sample 1130 in the dispensing tip 1180. Examples of operation 1158 are described in further detail with reference to Figures 44-55.

[0549] In operation 1160, the sample integrity detection device 1112 determines whether the interferent level falls within a tolerance range. When the determined level is outside the tolerance range, aspiration of the sample 1130 into the dispensing tip 112 is deemed inappropriate. The tolerance range may vary depending on the type of sample and / or the type of interferent therein. In some embodiments, whether the determined interferent level falls within the tolerance range can be evaluated using a classification identifier or classifier, as described below.

[0550] If it is determined that the detected interferent level falls within the tolerance range ("yes" at operation 1160), method 1150 continues with the pre-determined next step. Otherwise ("no" at operation 1160), method 1150 proceeds to operation 1162.

[0551] In operation 1162, the sample integrity detection device 1112 flags the aspiration to indicate that the aspirated sample 1130 in the dispensing tip 1180 is not suitable for subsequent processing. In other embodiments, the entire test result using the aspirated sample can be flagged to indicate or suggest that the test result may be inappropriate. Alternatively, the sample integrity detection device 1112 operates to stop the associated testing or analysis process in the instrument 100. In other embodiments, the evaluation results can be used to automatically adjust test results that may be erroneous due to compromised sample quality.

[0552] 44-55, an example of operation 1158 of FIG. 43 is described, in which the captured image 1132 is analyzed to determine 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.

[0553] Figure 44 is a flowchart illustrating an example method 1170 of operating the image assessment device 1122 of Figure 42. In some embodiments, the method 1170 includes operations 1172, 1174, and 1176. The method 1170 is also described with reference to Figure 45, which illustrates an example analysis of a captured image 1132.

[0554] In operation 1172, the image evaluation device 1122 locates the dispensing tip 1180 in the image 1132. Various image processing methods can be used to detect the dispensing tip 1180 within the image 1132. In some embodiments, the dispensing tip 1180 is located by a pattern matching function that searches for a pattern representing the dispensing tip based on a pre-trained reference image. Such image processing methods can be implemented in various programming languages, such as Python (e.g., its contour finding function). One exemplary method of such an image processing method can be implemented by Cognex In-Sight Vision Software available from Cognex Corporation (Natick, MA), which provides various tools such as edge detection ("Edge"), pattern matching ("Pattern Match"), and histogram analysis ("Histogram").

[0555] In operation 1174, the image evaluation device 1122 detects a pre-determined region of interest 1182. The region of interest 1182 is a region of the image 1132 that is evaluated to determine the quality of the sample 1130 in the dispensing tip 1180. The region of interest 1182 is pre-set as a region that can be repeatedly detected as containing the sample 1130 in different images 1132. Various methods can be used to detect the region of interest 1182. One example of such a method is described with reference to FIG. 46. In some embodiments, there may be more than one pre-determined region of interest, and therefore the image evaluation device 1122 detects more than one pre-determined region of interest. For example, there may be three pre-determined regions of interest: a first region of interest above the region of interest 1182, a second region of interest such as the region of interest 1182, and a third region of interest below the region of interest 1182.

[0556] In operation 1176, the image evaluation device 1122 extracts color parameters 1134 (FIG. 42) of the captured image 1132. In some embodiments, a region of interest 1182 within the image 1132 is analyzed to generate the color parameters 1134. One example of extracting color parameters is described with reference to FIGS.

[0557] 46 is a flowchart illustrating an example method 1190 for finding a region of interest 1182 in an image 1132. In some embodiments, the method 1190 includes operations 1192 and 1194. The method 1190 is also described with reference to FIG.

[0558] Generally, once the location of the dispensing tip 1180 is determined, the image evaluation device 1122 uses a set of offset coefficients to determine a region of interest 1182. In some embodiments, the region of interest 1182 is optimized to include a subsection of the dispensing tip image that is approximately centered relative to the vertical and horizontal axes of the sample 1130 within the dispensing tip 1180, such that the region of interest 1182 is generally centered relative to the aspirated sample 1130. In other embodiments, other locations are possible for the region of interest 1182. In other embodiments, there may be more than one region of interest, as described above.

[0559] In operation 1192, the image evaluation device 1122 finds a reference line associated with the dispensing tip 1180. In some embodiments, the reference line is a vertical edge 1184 of the dispensing tip 1180 in the image 1132. Other lines on the dispensing tip 1180 can also be used as a reference line.

[0560] In operation 1194, the image evaluation device 1122 locates a region located away from the reference line 1184 by a pre-determined offset 1186. In some embodiments, the pre-determined offset 1186 determines the horizontal position of the region of interest 1182, while the vertical position of the region of interest 1182 is preset as a pre-determined height 1188 from the bottom of the image 1132. In some embodiments, the vertical position of the region of interest remains approximately the same between different images because the image capture unit is repeatedly aligned at the sample height relative to the dispensing tip.

[0561] One example of the image processing method used above can be implemented by Cognex In-Sight Vision Software available from Cognex Corporation (Natick, MA), which provides a variety of tools such as edge detection ("Edge"), pattern matching ("Pattern Match"), and histogram analysis ("Histogram").

[0562] 47 is a flowchart of an example method 1210 for extracting color parameters of an image 1132. The method 1210 is also described with reference to FIG. 48, which illustrates an example histogram 1220 of the image 1132. In some embodiments, the method 1210 includes operations 1212 and 1214.

[0563] In operation 1212, the image assessment device 1122 generates a histogram 1220 for the image 1132. In some embodiments, the histogram 1220 is generated from data for the regions of interest 1182 in the image 1132. In some embodiments, there is more than one region of interest, and therefore the image assessment device 1122 generates a histogram 1120 for each region of interest in the image 1132. For example, if there are three regions of interest in the image 1132, the image assessment device 1122 generates three separate histograms.

[0564] As illustrated in FIG. 48, histogram 1220 represents the distribution of different colors within image 1132 (e.g., its region of interest 1182). In some embodiments, histogram 1220 shows the number of pixels that have a color within each of a fixed list of color ranges (also referred to herein as bins). 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.

[0565] The histogram 1220 can be generated by first discretizing the colors (i.e., red, green, and blue in the RGB model) in the image 1132 (e.g., its region of interest 1182) into several bins and counting the number of pixels in each bin. For example, if the image 1132 is an 8-bit image, the values from 0 to 255 for each color are grouped into bins such that each bin contains 10 values. As an example, the first bin contains values equal to, greater than, and less than 10; the second bin contains values equal to, greater than, and less than 20; and the third bin contains values equal to, greater than, and less than 20. As illustrated in FIG. 48, 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, are depicted in the histogram 1220. In other embodiments, different color components in the RGB model, the CMYK color model, or any other color model can be used, hi other embodiments, the image can be different bit, 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.

[0566] In operation 1214, the image evaluation device 1122 obtains a plurality of color parameters 1134 from the histogram 1220. In some embodiments, the image evaluation device 1122 creates six color parameters. For example, the first color parameter 1232 is the average of the first color channel 1222, the second color parameter 1234 is the average of the second color channel 1224, and the third color parameter 1236 is the average 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, second, and third color channels 1222, 1224, and 1226 represent the areas under the curves of the first, second, and third color channels 1222, 1224, and 1226, respectively.

[0567] In other embodiments, other color parameters are generated from the histogram 1220. For example, the color parameters may include a maximum value of the first color channel 1222, a maximum value of the second color channel 1224, a maximum value of the third color channel 1226, a minimum value of the first color channel 1222, a minimum value of the second color channel 1224, a minimum value of the third color channel 1226, a mode of the first color channel 1222, a mode of the second color channel 1224, a mode of the third color channel 1226, a histogram head of the first color channel 1222, a histogram head of the second color channel 1224, a histogram head of the third color channel 1226, and the like. The histogram may include a histogram head for the first color channel 1222, a histogram tail for the second color channel 1224, a histogram tail for the third color channel 1226, a histogram head ratio for the first color channel 1222, a histogram head ratio for the second color channel 1224, a histogram head ratio for the third color channel 1226, a histogram tail ratio for the first color channel 1222, a histogram tail ratio for the second color channel 1224, and a histogram tail ratio for the third color channel 1226. The histogram head defines the minimum grayscale value of the histogram. For example, the histogram head for the first color channel 1222 defines the minimum grayscale value of the first color channel 1226 in the histogram. The histogram tail defines the maximum grayscale value of the histogram. For example, the histogram tail for the first color channel 1222 defines the maximum grayscale value of the first color channel 1226 in the histogram. The histogram head ratio defines the percentage of total pixels in the histogram that lie within a specified range of grayscale values having a minimum grayscale value. For example, the histogram head ratio of a first color channel 1222 defines the percentage of total pixels in the histogram of the first color channel 1222 that lie within a specified range of minimum grayscale values for the first color channel 1222. The histogram tail ratio defines the percentage of total pixels represented in the histogram that lie within a specified range of grayscale values having a maximum grayscale value.For example, the histogram tail percentage for the first color channel 1222 defines the percentage of the total pixels of the first color channel 1222 in the histogram that lie within a specified range of the highest grayscale value for the first color channel 1222.

[0568] In other embodiments, the color parameters include the average of the color channels (e.g., the first, second, and third color channels), the peak of the color channels (e.g., the first, second, and third color channels), and / or the standard deviation of the color channels (e.g., the first, second, and third color channels). In still other embodiments, other types of color parameters are also used.

[0569] Figure 49 is a flowchart of an exemplary method 1270 for operating the classification data generation device 1124 of Figure 42. Method 1270 is described with reference to Figures 50 and 51. Figure 50 is an exemplary t...

Claims

[Claim 1] The invention as described in the drawings of this application.

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