Identification method, pipetting method, storage medium, and sample processing system

Abstract

This application provides an identification method, comprising: acquiring an original image of a blood collection tube under blue light illumination; performing a channel separation operation on the original image to obtain a first image based on the signal of the green light channel and a second image based on the signal of the blue light channel, wherein the blood collection tube contains a centrifuged blood sample; identifying the total height of the centrifuged blood sample based on the grayscale distribution of the first image; and identifying the height of the white film layer in the centrifuged blood sample based on the grayscale distribution of the second image. This application also provides a pipetting method, a storage medium, and a sample processing system.

Description

Technical Field

[0001] This application relates to the field of pipetting technology, and in particular to a method for high-resolution identification of centrifuged blood samples, a pipetting method, a storage medium, and a sample processing system. Background Technology

[0002] After centrifugation, different components in a blood sample will separate into layers. In a blood sample tube, the centrifuged blood sample, from top to bottom, consists of a plasma layer, a leukocyte layer (also known as the white membrane layer), and a erythrocyte layer. A pipette can be used to aspirate the white membrane layer from the centrifuged blood sample. Before aspirating, the height of the white membrane layer needs to be identified to control the displacement of the pipette. Therefore, the entire process involves two stages: identification and aspiration.

[0003] Traditional identification methods simply rely on grayscale changes to determine liquid layering, resulting in inconsistent accuracy. Furthermore, the labels on the back of standard blood collection tubes significantly interfere with grayscale identification, increasing the risk of misjudgment. Additionally, under high-brightness light, the white film interface may exhibit multiple layers (see...). Figure 11 ), unable to locate accurately.

[0004] Traditional liquid aspiration processes directly absorb a certain volume of the white film at a single point, causing the white film layer to become concave at the aspiration point, resulting in an actual absorption rate of less than 30%. Furthermore, the spiral aspiration logic for the white film varies, and the actual aspiration effect is not ideal. Summary of the Invention

[0005] The first aspect of this application provides an identification method, comprising: acquiring an original image of a blood collection tube under blue light illumination; performing a channel separation operation on the original image to obtain a first image based on a signal from a green light channel and a second image based on a signal from a blue light channel, wherein the blood collection tube contains a centrifuged blood sample; identifying the total height of the centrifuged blood sample based on the grayscale distribution of the first image; and identifying the height of the white film layer in the centrifuged blood sample based on the grayscale distribution of the second image.

[0006] A second aspect of this application provides a pipetting method, comprising: acquiring an original image of a blood collection tube under blue light illumination; performing a channel separation operation on the original image to obtain a first image based on a signal from a green light channel and a second image based on a signal from a blue light channel, wherein the blood collection tube contains a centrifuged blood sample; identifying the total height of the centrifuged blood sample based on the grayscale distribution of the first image; identifying the height of a white film layer in the centrifuged blood sample based on the grayscale distribution of the second image; and aspirating a predetermined volume of white film based on the total height of the centrifuged blood sample and the height of the white film layer.

[0007] A third aspect of this application provides a readable storage medium storing a computer program that, when executed, implements the steps of the identification method or the pipetting method described above.

[0008] A fourth aspect of this application provides a sample processing system, comprising: a carrier for loading and fixing blood collection tubes, the carrier having at least two marker points, the blood collection tubes containing centrifuged blood samples; a light source for emitting blue stripe light to illuminate the blood collection tubes and the carrier; and a pipetting device, comprising: an imaging module for capturing an original image of the blood collection tube under blue light illumination, performing a channel separation operation on the original image to obtain a first image based on a signal from a green light channel, and obtaining a second image based on a signal from a blue light channel; an identification module for identifying the total height of the centrifuged blood sample based on the grayscale distribution of the first image, and identifying the height of the white film layer in the centrifuged blood sample based on the grayscale distribution of the second image, converting the total height of the centrifuged blood sample and the height of the white film layer from pixel height to actual height based on the two marker points; and a pipetting module for moving a preset displacement based on the actual height to aspirate the white film from the centrifuged blood sample.

[0009] The aforementioned identification method, pipetting method, storage medium, and sample processing system, by capturing images of the blood collection tube under blue light illumination and acquiring first and second images based on different color light channels, allow the outlines of the centrifuged blood sample and the white film layer to be displayed in their clearest state. This improves the identification accuracy of the total height of the centrifuged blood sample and the height of the white film layer, thereby enhancing the aspiration accuracy of the subsequent aspiration process. Attached Figure Description

[0010] Figure 1 This is a schematic diagram of the sample processing system according to an embodiment of this application.

[0011] Figure 2 for Figure 1 Three-view drawing of the vehicle.

[0012] Figure 3 This is a flowchart of one step of the identification method according to an embodiment of this application.

[0013] Figure 4 This is a schematic diagram of the first image captured by the camera.

[0014] Figure 5 This is a flowchart of another step of the identification method according to an embodiment of this application.

[0015] Figure 6 This is a schematic diagram of the second image acquired by the camera.

[0016] Figure 7 This is a flowchart of another step of the identification method according to an embodiment of this application.

[0017] Figure 8 This is a schematic diagram of the second image used to identify the lower interface of the white film layer.

[0018] Figure 9 A schematic diagram of the original image after identifying the total height of the centrifuged blood sample and the upper and lower boundaries of the white film layer.

[0019] Figure 10 This is a flowchart illustrating the steps of the pipetting method according to an embodiment of this application.

[0020] Figure 11 This is a schematic diagram of images of blood collection tubes and centrifuged blood samples obtained in a traditional high-white-light environment.

[0021] Figure 12 This is a schematic diagram of the upper boundary of the white film layer.

[0022] Explanation of main component symbols Sample processing system: 100; Pipetting equipment: 1; Shooting module: 10; Recognition module: 20; Pipetting module: 30; Vehicles: 2; Card slot: 201; Marker point: 202; Light source: 3; Blood collection tubes: 200; Tag: 21; Centrifuged blood sample: 300; Steps: S1, S2, S3, S21, S22, S23, S31, S32, S33, S201, S202, S203, S204; First image: P1; First boundary: P11; Second boundary: P12; Second image: P2; Launch direction: L1; Vertical direction: L2.

[0023] The following detailed description, in conjunction with the accompanying drawings, will further illustrate this application. Detailed Implementation

[0024] This application provides a pipetting device and a sample processing system including the pipetting device. The pipetting device can be used to identify the total height of a centrifuged blood sample and the height of the white film layer within the sample, and can also be used to aspirate the white film for subsequent use as a biological sample (e.g., gene sequencing). The pipetting device and sample processing system of this application improve identification accuracy and white film absorption rate.

[0025] Please see Figure 1 The sample processing system 100 of this application embodiment includes a pipetting device 1, a carrier 2, and a light source 3.

[0026] Please see Figure 2 The carrier 2 has multiple slots 201, each slot 201 for fixing a blood collection tube 200. Corresponding to each slot 201, the carrier 2 has two marker points 202 spaced apart vertically (perpendicular to the ground, tabletop, or any other surface on which the carrier 2 is placed). The two marker points 202 are located at 15mm and 40mm respectively (the bottom position of the blood collection tube 200 when placed in the slot 201 is 0mm). When the blood collection tube 200 is placed in the slot 201, this vertical direction is also the length extension direction of the blood collection tube 200. In this embodiment, the number and height of the marker points 202 corresponding to each slot 201 are the same. In other embodiments of this application, more marker points 202 may be provided on the carrier 2.

[0027] Please refer to the following: Figure 1 In this embodiment, the light source 3 is an array of light-emitting diodes (LEDs) used to emit strip-shaped blue light to illuminate the carrier 2 containing the blood collection tube 200. The pipetting device 1 is used to photograph the blood collection tube 200 and the carrier 2, and to process the acquired images to obtain the total height of the centrifuged blood sample in the blood collection tube 200 and the height of the white film layer in the centrifuged blood sample. The pipetting device 1 can move mechanically within a three-dimensional space defined by the XYZ axes and can perform aspiration operations along the aspiration axis. In this embodiment, the aspiration axis is parallel to the Z-axis and parallel to the aforementioned vertical direction. The pipetting device 1 is also used to make mechanical movements with corresponding displacements based on the total height of the centrifuged blood sample and the height of the white film layer, and to aspirate the white film. In this embodiment, the sample processing system 100 also includes a light source (not shown) for emitting strip-shaped white light, so that white light and blue light jointly illuminate the blood collection tube 200 and the carrier 2.

[0028] In this embodiment, the pipetting device 1 includes an imaging module 10, an identification module 20, and a pipetting module 30. The identification module 20 is electrically connected to both the imaging module 10 and the pipetting module 30. The imaging module 10 is a color camera with three imaging channels (red, green, and blue, respectively for acquiring red, green, and blue light signals for imaging), used to capture images of the blood collection tube and the carrier 2 under blue light illumination. The identification module 20 may include a circuit board, a chip, etc., used to identify the total height of the centrifuged blood sample and the height of the white film layer in the image acquired by the imaging module 10. The pipetting module 30 may include a multi-channel pipetting array, used to perform mechanical movement and pipetting operations based on the total height of the centrifuged blood sample and the height of the white film layer obtained by the identification module 20, to aspirate the white film inside the blood collection tube.

[0029] This application also provides an identification method applied in a pipetting device 1. Please refer to... Figure 3 The above identification method includes the following steps: Step S1: Obtain the original image of the blood collection tube under blue light illumination, perform a channel separation operation on the original image to obtain a first image based on the signal of the green light channel and a second image based on the signal of the blue light channel. The blood collection tube contains centrifuged blood sample. Step S2: Identify the total height of the centrifuged blood sample based on the grayscale distribution of the first image; and Step S3: Identify the height of the white film layer in the centrifuged blood sample based on the grayscale distribution of the second image.

[0030] Before step S1 in this embodiment, the light source 3 emits blue light diagonally downwards or directly downwards. The angle θ between the blue light emission direction L1 and the vertical direction L2 can be 0°-15° (including the endpoint value). In this embodiment, the light source 3 is located between the blood collection tube 200 and the imaging module 10. That is, the light source 3 illuminates the front of the blood collection tube 200, so that the blood collection tube 200 and the carrier 2 are under the blue light illumination.

[0031] In this embodiment, the operating parameters of the imaging module 10 (including exposure value, gamma value, white balance, gain, etc.) are adjustable. In step S1, the exposure value of the imaging module 10 is adjusted and the gamma value of the imaging module 10 is increased. Automatic white balance is turned off, and the gain of the green and blue channels is set to be greater than the gain of the red channel. The exposure value of the imaging module 10 is between 10000 and 25000 (inclusive). The gamma value is adjusted to achieve the highest contrast in the image captured by the imaging module 10. After adjusting the operating parameters of the imaging module 10, the imaging module 10 captures the original image including the blood collection tube 200 and the carrier 2 under blue light illumination.

[0032] The original image is a color image generated based on blue, green, and red light in the environment captured by the lens in the imaging module 10. Therefore, the original image includes at least a first image generated based on the signal from the green light channel and a second image generated based on the signal from the blue light channel.

[0033] In this embodiment, the first image obtained is as follows: Figure 4 As shown, Figure 4 The first image P1 in this embodiment shows a carrier 2 and two blood collection tubes 200. Both blood collection tubes 200 contain centrifuged blood samples 300. In other embodiments of this application, fewer or more blood collection tubes 200 can be captured simultaneously, meaning the first image P1 includes fewer or more blood collection tubes 200. Furthermore, in this embodiment, to distinguish different centrifuged blood samples, a label 21 is affixed to the blood collection tube 200. The label 21 is rectangular and affixed to the highest point of the blood collection tube 200.

[0034] Please see Figure 5 In this embodiment, step S2 includes: Step S21: Starting from the first edge of the first image, the pixel height of the first row of pixels is calculated as h1; Step S22: Calculate the sum of the first gray levels of all pixels within the range of (h1+Δh1), and calculate the sum of the second gray levels within the range of (h1+Δh1+1) to (h1+2Δh1); Step S23: Identify the total height of the centrifuged blood sample based on the first gray level difference between the first gray level sum and the second gray level sum.

[0035] Please refer to the following: Figure 4 The first image P1 is a rectangular image with a first boundary P11 and a second boundary P12 that are parallel to each other. The opening of the blood collection tube 200 in the first image P1 faces the first boundary P11. The first image P1 includes multiple rows of pixels arranged sequentially from the first boundary P11 to the second boundary P12, and the direction from the first boundary P11 to the second boundary P12 is defined as the first direction.

[0036] In step S21, starting from the first boundary P11, the pixel height of the first row of pixels is recorded as h1. Along the first direction, the pixel heights of each row of pixels are h1+1, h1+2, h1+3, etc.

[0037] In step S22, the sum of the brightness of all pixels within the range (h1 + Δh1) is calculated as the first grayscale sum, and the sum of the brightness of all pixels within the range (h1 + Δh1 + 1) to (h1 + 2Δh1) is calculated as the second grayscale sum. In this embodiment, Δh1 is 10. That is, in step S22, starting from pixel height h1, the sum of the brightness of pixels in rows 1 to 10 of the first image P1 is calculated as the first grayscale sum, and the sum of the brightness of pixels in rows 11 to 20 of the first image P1 is calculated as the second grayscale sum.

[0038] In step S23, the first gray level difference between the first gray level sum and the second gray level sum is calculated: First gray level difference = First gray level sum - Second gray level sum. It is then determined whether this first gray level difference is greater than or equal to a first threshold. If yes, the current pixel height h1 is recorded as the total height H1 of the centrifuged blood sample; if no, h1 = h1 + 1, that is, the pixel height of the next row of pixels in the first direction is recorded as the new h1, and step S22 continues.

[0039] For example, in the current time period, if the pixel height of the first row of pixels is h1, and the calculated first grayscale difference is less than the first threshold, then the pixel height of the second row of pixels is set to h1, and the first grayscale difference is calculated and compared with the first threshold. This process is repeated until the first grayscale difference is greater than or equal to the first threshold. For example, in a certain time period, if the pixel height of the 20th row of pixels is denoted as h1, and the calculated first grayscale difference is greater than or equal to the first threshold, then the pixel height of the 20th row of pixels is considered to be h1, which is the total height H1 of the centrifuged blood sample.

[0040] like Figure 4 As shown, the brighter portion of the first image P1 corresponds to the location of label 21, while the darker portion corresponds to the location of centrifuged blood sample 300 inside the blood collection tube 200. When h1 gradually moves downwards from top to bottom and calculates the first grayscale sum and the second grayscale sum, if the pixels in the darker portion have already been included in the pixel range for calculating the grayscale sum, the calculated second grayscale sum will suddenly decrease. Therefore, the first grayscale difference value = first grayscale sum - second grayscale sum will suddenly increase.

[0041] According to the experiment, a first threshold is preset. When the difference between the first gray levels is less than the first threshold, the difference between the sum of gray levels is considered to be within a reasonable range, and in this case, the value is moved down by h1.

[0042] When the first grayscale difference is greater than or equal to the first threshold, it is considered that the total grayscale value has decreased drastically, and it is determined that the location of the centrifuged blood sample 300 has been reached. The value h1 at this point is recorded as the total height H1 of the centrifuged blood sample 300, where the total height refers to the pixel height. That is, the total height H1 obtained at this point represents the pixel sequence in the first image P1, not the actual height in three-dimensional space. For example, if h1 is 30, it indicates that the total height of the centrifuged blood sample 300 is located at the 30th row of pixels in the first image P1.

[0043] In at least one embodiment of this application, before executing step S21, the first image is binarized according to a preset grayscale value. The preset grayscale value can be taken from 150-210 (including endpoint values), for example, the preset grayscale value is set to 180. That is, the grayscale values ​​of all pixels in the first image with a grayscale value greater than 180 are converted to a maximum grayscale value (e.g., 255), and the grayscale values ​​of all pixels in the first image with a grayscale value less than or equal to 180 are converted to a minimum grayscale value (e.g., 0), so that the binarized first image presents an overall black and white effect.

[0044] Thus, the contrast of each part in the binarized first image is higher, and the boundary of the centrifuged blood sample 300 is clearer. Based on the binarized first image, subsequent steps S21-S23 are performed to obtain a more accurate total height H1 of the centrifuged blood sample.

[0045] Typically, the height of the centrifuged blood sample 300 is below the highest point of the tag 21. Under downward blue bar light illumination, in the first image P1 generated based on the green light signal, the gray value of the tag 21 is very high (above 250), while the gray value of the centrifuged blood sample 300 is generally below 150. Therefore, the height H1 of the centrifuged blood sample 300 can be easily identified based on the first image P1. Using a 1-pixel step, the liquid surface position of the centrifuged blood sample 300 can be captured as accurately as possible.

[0046] In this embodiment, the second image P2 is as follows: Figure 6 As shown, according to Figure 4 and Figure 6 It can be seen that the interface of the total height of the centrifuged blood sample 300 can be clearly distinguished in the first image P1, while the layered interface of the centrifuged blood sample 300 itself can be clearly distinguished in the second image P2. Step S3 mainly determines the height of the white film layer in the centrifuged blood sample 300 based on the second image P2.

[0047] In this embodiment, please refer to Figure 7 Step S3 includes: Step S31: Based on the total height of the centrifuged blood sample, a portion of the second image is cropped as the white film recognition area; Step S32: Identify the candidate height of the white film layer based on the grayscale change of the center pixel of each row of pixels within the white film recognition area; Step S33: Using the candidate height as a reference, binarize the grayscale values ​​of pixels within a preset range on both sides of the candidate height to capture the outline of the white film layer.

[0048] In step S31, based on the total height H1 of the centrifuged blood sample, a region in the second image P2 located between 35% and 80% of the total height of the centrifuged blood sample 300 is selected as the white film recognition region. The specific range of 35%-80% is determined according to the content and distribution area of ​​each component in the centrifuged blood sample 300. In at least one embodiment of this application, in step S31, a region in the second image P2 located between 35% and 55% of the total height of the centrifuged blood sample 300 may be selected as the white film recognition region.

[0049] The aforementioned white film recognition region has an upper boundary and a lower boundary. The upper and lower boundaries are parallel to the first boundary P11 and the second boundary P12. The white film recognition region includes multiple rows of pixels arranged sequentially from the upper boundary to the lower boundary.

[0050] In this embodiment, step S32 includes: Step S321: Starting from the lower boundary, record the pixel height of the row of pixels closest to the lower boundary as h2. In the second direction from the lower boundary to the upper boundary, the pixel heights of each row of pixels are h2-1, h2-2, h2-3, etc. Step S322: Calculate the third gray value of multiple central pixels (e.g., 16 central pixels) within the range of (h2-Δh2); Step S323: Determine whether the total third gray value is greater than or equal to the second threshold. If the total third gray value is greater than or equal to the second threshold, record the pixel height (h2-Δh2) at this time as the candidate height H2 of the white film layer. If the total center gray value is less than the second threshold, record the pixel height of the previous row as the new h2, that is, let h2=h2-1, and execute step S322 again until the total third gray value is greater than or equal to the second threshold, and confirm the candidate height H2.

[0051] In this embodiment, Δh2 is 30, which is the total gray value of the center pixels of the adjacent 30 rows of pixels calculated in step S322. In this embodiment, Δh2 is greater than Δh1 because the boundary of the white film layer may be tilted (see...). Figure 12 This means that its actual height may be within a large range.

[0052] In this embodiment, since a label 21 is also attached to the blood collection tube 200, and the height area covered by the label 21 may overlap with the height area of ​​the white film layer, and the label 21 is generally attached to the middle position of the blood collection tube 200 in the horizontal direction, there may be a situation where the outline of the label 21 interferes with the identification of the boundary outline of the white film layer. Therefore, in step S3, when calculating the third gray value of the central multiple pixels of each row of pixels, the central multiple pixels are taken from the pixels after removing the label pixels.

[0053] For example, a row of pixels includes 1000 pixels, with the center 16 pixels being pixels 493-508. If label interference is detected, and the label occupies the center 100 pixels, then the center 16 pixels selected in step S3 are pixels 443-450 and 551-558. In step S33, after determining the candidate height H2 (h2-Δh2), using the candidate height H2 as a reference, a height range of ±Δh3 above and below the candidate height H2 is extracted. The average gray value of the middle pixel of each row within this height range is calculated as -3 and binarized to capture the outline of the white film layer and obtain the height H3 of the white film layer. Figure 8 As shown. In this embodiment, Δh3 = 5mm. Figure 9 The original image shows the total height H1 and the height H3 of the white film layer of the centrifuged blood sample 300.

[0054] In this embodiment, the outline of the white film layer identified in the above image includes the upper interface and the lower interface of the white film layer. In other embodiments of this application, the outline of the white film layer identified in the above image includes an upper interface, a lower interface, a left interface, and a right interface; the upper interface, left interface, lower interface, and right interface are sequentially connected to form the complete outline of the white film layer. The left interface and the right interface are determined by grasping the widest part.

[0055] In at least one embodiment of this application, due to the presence of the label, the upper boundary of the white film layer may be partially obscured in the center, and only the two ends of the upper boundary can be identified (i.e., white interference exists). Therefore, after step S33, the method further includes: filling the boundary contour of the captured white film layer with a grayscale value of 255; scanning the number of pixels with consecutive grayscale values ​​of 255; confirming the presence of white interference at the upper boundary of the white film layer when the number of pixels with consecutive grayscale values ​​of 255 in each row within the white film identification area conforms to a preset trend; and performing empirical fitting to complete the upper boundary of the white film layer. In this embodiment, the main consideration is that the label will obscure the upper boundary portion of the captured white film layer's boundary contour; therefore, filling the boundary contour of the white film layer mainly involves filling the upper boundary of the white film layer.

[0056] When there is no label interference, during the movement along the second direction (from bottom to top), the number of consecutive pixels with a grayscale value of 255 in each row of pixels scanned (or captured) follows a pattern of first gradually increasing to a number w1, and then gradually decreasing to a number w2. That is, when there is no label interference, during the bottom-to-top scanning process, the number of pixels with consecutive grayscale values ​​of 255 in each row shows a trend of first increasing and then decreasing. In this embodiment, w2 < 0.6 * w1.

[0057] When label interference is present, the trend of the number of pixels with consecutive grayscale values ​​of 255 in each row changes. Specifically, during the movement along the second direction, the number of pixels with consecutive grayscale values ​​of 255 in each row first gradually increases to w1, then gradually decreases to w2, and then gradually increases to w3. In other words, when label interference is present, during the bottom-to-top scanning process, the number of pixels with consecutive grayscale values ​​of 255 in each row exhibits a trend of first increasing, then decreasing, and then increasing again.

[0058] Therefore, in this embodiment, the variation pattern of the number of pixels with consecutive 255 grayscale values ​​is used to determine whether there is label interference during the process of identifying the height of the white film layer.

[0059] In this embodiment, when it is determined that there is label interference, the pixel height of the two rows of pixels with consecutive 255 gray values ​​equal to w1 and w2 is used for empirical fitting to fit the upper boundary of the white film layer, and the upper boundary contour of the white film layer that is blocked by the label is completed to obtain the height H3 of the white film layer.

[0060] During the white film identification process, due to the presence of label 21, the outline of label 21 with a larger grayscale value will clearly appear in the plasma layer position far from the white film layer. Therefore, choosing to search the boundary of the white film layer from bottom to top can remove the label's influence. Since the position of the white film layer is not strictly horizontal, a local range is used, with a spacing of 30 pixels and a step of 1 pixel at a time, taking 16 pixels per row to find the position with the largest grayscale change. Under blue light illumination, the normal white film layer will have a thicker white film area in the middle position. Therefore, the white film identified in this embodiment is the grayscale value of the main body of the white film. Due to the gamma enhancement and blue light gain enhancement, the contrast of the white film layer position can be effectively improved. The grayscale value of the white film is very uniform, and the back label near the white film layer will also be illuminated to a smaller grayscale value. After local binarization, the outline of the white film can be easily identified.

[0061] In this embodiment, the total height of the centrifuged blood sample and the height of the white film layer obtained in steps S2 and S3 are pixel heights. After step S3, based on the actual height of the marker point 202 on the carrier 2 stored in advance, the total height of the centrifuged blood sample and the height of the white film layer are converted from pixel heights to actual heights. This actual height can be used to feedback control the actual displacement of the pipetting module 30 in the three-dimensional space XYZ axis during the aspiration process, and can also be used to feedback control the actual displacement of the aspiration axis of the pipetting module 30. That is, the pipetting module 30 performs four-axis linkage of XYZ and aspiration axis based on the total height H1 of the centrifuged blood sample and the height H3 of the white film layer to aspirate a target volume (e.g., 1000 μl) of white film.

[0062] This application also provides a pipetting method applied in a pipetting apparatus 1. Please refer to [link to relevant documentation]. Figure 10 The pipetting method includes: Step S201: Obtain the original image of the blood collection tube under blue light illumination, perform a channel separation operation on the original image to obtain a first image based on the signal of the green light channel and a second image based on the signal of the blue light channel. The blood collection tube contains centrifuged blood sample. Step S202: Identify the total height of the centrifuged blood sample based on the grayscale distribution of the first image; Step S203: Identify the height of the white film layer in the centrifuged blood sample based on the grayscale distribution of the second image; the total height of the centrifuged blood sample and the height of the white film layer are used for feedback control of the liquid aspiration process; and Step S204: Take a preset volume of white film based on the total height of the centrifuged blood sample and the height of the white film layer.

[0063] In the pipetting method of this embodiment, step S201 can refer to step S1 in the above-described identification method, step S202 can refer to step S2 in the above-described identification method, and step S203 can refer to step S3 in the above-described identification method, and will not be described again. In traditional methods of aspirating the white film, single-point aspiration can easily create a depression in the white film layer (the plasma layer on top of the white film layer sinks into the white film layer). In this embodiment, step S204 first adjusts the displacement of the pipetting module 30 in the Z-axis direction according to the total height H1 of the centrifuged blood sample, so that the pipetting module 30 first aspirates the uppermost plasma layer until the plasma layer thickness decreases to 2-3 mm (including the endpoint value) and then stops aspiration. After the plasma layer aspiration is completed, the displacement of the pipetting module 30 in the Z-axis direction is adjusted according to the height H3 of the white film layer, so that the pipette tip stops at the preset height position of the white film layer, and the pipetting module 30 is adjusted to move in the X-axis and Y-axis planes to aspirate the white film at multiple points in the white film layer sequentially.

[0064] The nozzle of a pipette tip is typically circular, and different aspiration methods can be used depending on the nozzle diameter. For wide-nose pipette tips with a larger nozzle diameter, the aspiration points in the white film layer can include multiple points evenly spaced along the circumference and a single point at the center. For narrow-nose pipette tips with a smaller nozzle diameter, the aspiration points in the white film layer can include multiple points evenly spaced along the circumference of multiple concentric circles of different diameters and a single point at the center. In other words, for wide-nose pipette tips, a "large circle + center" method can be used for aspiration, while for narrow-nose pipette tips, a "large circle + small circle + center" method can be used. The more aspiration points, the smoother the aspiration process.

[0065] In this embodiment, the pipetting module 30 starts aspirating from 2 mm below the highest point of the white film. The pipetting module 30 aspirates a total of m microliters (μl) of white film at n points, where n-1 points are equidistant on the circumference, and the other point is located at the center of the blood collection tube. The volume of white film aspirated by the pipetting module 30 at the aforementioned n-1 points is equal, and the volume of white film aspirated at the center of the blood collection tube is twice the volume aspirated at any other single point. Therefore, the volume of white film aspirated by the pipetting module 30 at any single point among the aforementioned n-1 points is: .

[0066] In at least one embodiment of this application, the pipetting module 30 uses a wide-mouth pipette tip with an outer diameter of 6 mm to spirally aspirate 800 μl of white film inside a blood collection tube with an inner diameter of 13 mm, with 18 aspiration points per layer. Seventeen points are evenly spaced on a circle with a radius of 3 mm, and one point is located at the center. In this embodiment, the aspiration height is less than 6 mm, the aspiration volume at each point is 13.3333 µl, and the required aspiration volume per layer is 266.6667 µl. In actual operation, the decimal part of the data needs to be discarded, i.e., the aspiration volume at each point is 13 µl. The first and second circles move to the center at the end, aspirating 32 µl to complete the 266 µl volume. The last circle moves to the center, aspirating 34 µl to complete the 800 µl aspiration volume. The aspiration volume is 6 mm, so the actual movement range is from 4 mm below the highest liquid level to 6 mm below the center. The entire process requires ensuring that there is as little empty suction as possible, so that the white film layer can be extracted more completely.

[0067] In this embodiment, the height at which the pipetting module 30 picks up the white film is such that after the step of picking up the white film is completed, the upper boundary of the white film layer is higher than the pipette tip opening, and the height above the pipette tip opening is kept less than 0.1 mm.

[0068] The identification method, pipetting method, pipetting device 1, and sample processing system 100 of the above embodiments of this application, by capturing images of blood collection tubes under blue light illumination and acquiring first and second images based on different color light channels, allow the outlines of the centrifuged blood sample and the white film layer to be displayed in their clearest state. This improves the identification accuracy of the total height of the centrifuged blood sample and the height of the white film layer, thereby improving the aspiration accuracy of the subsequent aspiration process.

[0069] In addition, in this embodiment, the plasma on the white membrane layer is first aspirated, and then the white membrane is aspirated by spiral circumferential suction, which can avoid the formation of depression areas on the white membrane layer and help improve the absorption rate of the white membrane.

[0070] This application also provides a non-volatile computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of any of the above-described identification methods or pipetting methods.

[0071] When the above-described identification method is implemented and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above-described embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of any of the above-described identification methods or pipetting methods. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable storage medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0072] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. This processor is the control center of the sample processing system, connecting all parts of the system via various interfaces and lines.

[0073] The memory is used to store the computer programs and / or modules. The processor implements various functions of the sample processing system by running or executing the computer programs and / or modules stored in the memory and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0074] Those skilled in the art should recognize that the above embodiments are only used to illustrate this application and are not intended to limit this application. Any appropriate changes and variations made to the above embodiments within the essential spirit and scope of this application fall within the scope of protection claimed in this application.

Claims

1. A recognition method, characterized in that, include: The original image of the blood collection tube under blue light illumination is acquired, and a channel separation operation is performed on the original image to obtain a first image based on the signal of the green light channel and a second image based on the signal of the blue light channel. The blood collection tube contains centrifuged blood sample. The total height of the centrifuged blood sample is identified based on the grayscale distribution of the first image; as well as The height of the white film layer in the centrifuged blood sample is identified based on the grayscale distribution of the second image.

2. The identification method as described in claim 1, characterized in that, The first image is a rectangular image with a first boundary and a second boundary that are parallel to each other. The opening of the blood collection tube in the first image faces the first boundary. The first image includes multiple rows of pixels arranged sequentially from the first boundary to the second boundary. The step of identifying the total height of the centrifuged blood sample based on the grayscale distribution of the first image includes: Starting from the first boundary of the first image, the pixel height of the first row of pixels is calculated as h1; Calculate the sum of the first gray levels of all pixels within the range (h1+Δh1), and calculate the sum of the second gray levels within the range (h1+Δh1+1) to (h1+2Δh1); When the first gray level difference is greater than or equal to the first threshold, (h1+Δh1+1) is recorded as the total height H1 of the centrifuged blood sample.

3. The identification method as described in claim 2, characterized in that, Before the step of calculating the pixel height h1 of the first row of pixels starting from the first edge of the first image, the method further includes: The grayscale values ​​of each pixel in the first image are binarized using preset grayscale values; The step of calculating the pixel height h1 of the first row of pixels starting from the first boundary of the first image includes: Starting from the first boundary of the binarized first image, the pixel height of the first row of pixels is calculated as h1.

4. The identification method as described in claim 1, characterized in that, The step of identifying the height of the white film layer in the centrifuged blood sample based on the grayscale distribution of the second image includes: Based on the total height H1 of the centrifuged blood sample, a portion of the second image is extracted as the white film recognition area; The candidate height of the white film layer is identified based on the grayscale variation of the center pixel of each row of pixels within the white film recognition area; Using the candidate height as a reference, the grayscale of the pixels within a preset range above and below the candidate height is binarized.

5. The identification method as described in claim 4, characterized in that, The step of cropping a portion of the second image as the white film recognition region includes: The area in the second image that is between 35% and 80% of the total height of the centrifuged blood sample from top to bottom is selected as the white film recognition area.

6. The identification method as described in claim 4, characterized in that, The white membrane recognition area has a lower boundary and an upper boundary that are parallel to each other. The upper boundary is located on the side where the opening of the blood collection tube is located. The white membrane recognition area includes multiple rows of pixels arranged sequentially from the lower boundary toward the upper boundary. The step of identifying the candidate height of the white film layer based on the grayscale variation of the center pixel of each row of pixels within the white film recognition area includes: Starting from the lower boundary, the pixel height of the first row of pixels is denoted as h2; Calculate the total gray value of the central pixels within the range of (h2-Δh2); Move the pixel height h2 row by row and continuously calculate the third gray value of multiple central pixels within the range of (h2-Δh2); When the total third gray value is greater than the second threshold, the pixel height (h2-Δh2) is recorded as the actual height of the white film layer.

7. The identification method as described in claim 6, characterized in that, The step of calculating the total third gray value of multiple central pixels within the range of (h2-Δh2) includes: Calculate the total third gray value of the center pixels outside the label pixels of each row within the range of (h2-Δh2).

8. The identification method as described in claim 4, characterized in that, The step of binarizing the grayscale of pixels within a preset range above and below the candidate height, based on the candidate height, includes: Using the candidate height as a reference, the average gray value of the middle pixel of each row of pixels within the height range of Δh3 above and below the candidate height is obtained as -3, and then binarized to obtain the height H3 of the white film layer.

9. The identification method as described in claim 4, characterized in that, Following the binarization step, the following is also included: The boundary contour of the captured white film layer is filled with a gray value of 255; The number of pixels with consecutive 255 grayscale values ​​scanned; When the number of pixels with consecutive 255 grayscale values ​​in each row within the white film recognition area conforms to a preset trend, it is confirmed that white interference exists at the upper boundary of the white film layer; and Empirical fitting is performed to complete the upper boundary of the white film layer.

10. The identification method according to any one of claims 1-9, characterized in that, The step of acquiring the original image of the blood collection tube under blue light illumination includes: Acquire original images of blood collection tubes and the carrier that holds the blood collection tubes under blue light illumination, wherein the carrier is provided with at least two marker points; After the step of calculating the height of the white film layer in the centrifuged blood sample based on the grayscale distribution of the second image, the method further includes: Based on the at least one marker point, the total height of the centrifuged blood sample and the height of the white film layer are converted from pixel height to actual height.

11. A pipetting method, characterized in that, include: The original image of the blood collection tube under blue light illumination is acquired, and a channel separation operation is performed on the original image to obtain a first image based on the signal of the green light channel and a second image based on the signal of the blue light channel. The blood collection tube contains centrifuged blood sample. The total height of the centrifuged blood sample is identified based on the grayscale distribution of the first image; The height of the white film layer in the centrifuged blood sample is identified based on the grayscale distribution of the second image; as well as A predetermined volume of white film is drawn based on the total height of the centrifuged blood sample and the height of the white film layer.

12. The pipetting method as described in claim 11, characterized in that, The centrifuged blood sample includes a plasma layer located on the white membrane layer; The step of extracting a predetermined volume of white film based on the total height of the centrifuged blood sample and the height of the white film layer includes: Based on the total height of the centrifuged blood sample, the plasma layer is extracted; Based on the height of the white film layer, white film is extracted at multiple points in the white film layer, and at least some of the multiple points are equidistant in the circumferential direction.

13. A readable storage medium, characterized in that, The device contains a computer program that, when executed, implements the identification method as described in any one of claims 1-10, or the pipetting method as described in claim 11 or 12.

14. A sample processing system, characterized in that, include: A carrier for loading and securing blood collection tubes, the carrier having at least two marking points, the blood collection tubes containing centrifuged blood samples; A light source is used to emit blue stripes of light to illuminate the blood collection tube and the carrier; as well as Pipetting equipment, including: The imaging module is used to capture the original image of the blood collection tube under blue light illumination, and to perform a channel separation operation on the original image to obtain a first image based on the signal of the green light channel and a second image based on the signal of the blue light channel. The recognition module identifies the total height of the centrifuged blood sample based on the grayscale distribution of the first image, and identifies the height of the white film layer in the centrifuged blood sample based on the grayscale distribution of the second image. Based on the two marker points, it converts the total height of the centrifuged blood sample and the height of the white film layer from pixel height to actual height. The pipetting module travels a preset displacement based on the actual height to aspirate the white film from the centrifuged blood sample.

Images