Cell concentration statistical method, device and system

Abstract

A method, apparatus, and system for calculating cell concentration are disclosed. The method includes: determining an effective measurement region of a cell container, the cell container including a first encapsulation layer, a second encapsulation layer, and a solution cavity disposed between the first and second encapsulation layers; a first positioning mark is disposed on one side of the first encapsulation layer facing the solution cavity, and a second positioning mark is disposed on one side of the second encapsulation layer facing the solution cavity; dividing the effective measurement region into multiple sub-regions; focusing and acquiring an image of each sub-region; detecting the number of cells in each image and summing the number of cells in multiple images to obtain the total number of cells in the effective measurement region; focusing on the first and second positioning marks to obtain a first original cavity thickness; multiplying the first original cavity thickness by a preset adjustment coefficient to obtain an adjusted cavity thickness; calculating the volume of the effective measurement region based on the adjusted cavity thickness; and calculating the cell concentration based on the total number of cells and the volume of the effective measurement region.

Description

Technical Field

[0001] This disclosure relates to, but is not limited to, the field of biomedical detection technology, and in particular to a method, apparatus and system for statistical analysis of cell concentration. Background Technology

[0002] In the biomedical field, cell counting is widely used in the detection of various cell indicators, such as white blood cell and red blood cell counts. With the continuous development of technology, cell counting techniques have evolved from manual counting to automated counting. Based on the detection principle, commonly used automated cell counting instruments can be broadly classified into three categories: counters based on the Coulter principle, flow cytometers, and image-based counters. Image-based counters, due to their advantages such as convenient detection, no need for fluorescent labeling, relatively low detection cost, and portability, represent a mainstream research direction in cell detection.

[0003] However, due to various reasons such as low quality of acquired cell images and dense cell overlap, image-based counters suffer from low accuracy. Summary of the Invention

[0004] This disclosure provides a cell concentration statistics method, apparatus, and system that can effectively improve the accuracy of cell concentration statistics using image-based counters.

[0005] This disclosure provides a method for cell concentration statistics, including: The effective measurement area of ​​the cell container to be tested is determined, and the effective measurement area is divided into multiple sub-regions. Each sub-region is focused and an image is acquired by an image acquisition device. The cell container to be tested includes a first encapsulation layer, a second encapsulation layer, and a solution cavity disposed between the first encapsulation layer and the second encapsulation layer. A first positioning mark is provided on one side of the first encapsulation layer facing the solution cavity, and a second positioning mark is provided on one side of the second encapsulation layer facing the solution cavity. The number of cells in the image of each sub-region is detected, and the number of cells in the images of multiple sub-regions is summed to obtain the total number of cells in the effective measurement region; The first positioning mark is focused using the image acquisition device to obtain a first image acquisition height; the second positioning mark is focused using the image acquisition device to obtain a second image acquisition height; the difference between the first image acquisition height and the second image acquisition height is calculated to obtain a first original cavity thickness; the first original cavity thickness is multiplied by a preset adjustment coefficient to obtain an adjusted cavity thickness; the volume of the effective measurement area is calculated based on the adjusted cavity thickness. The cell concentration is calculated based on the total number and volume of cells in the effective measurement area.

[0006] This disclosure also provides a cell concentration counting device, including a memory; and a processor connected to the memory, the memory being used to store instructions, the processor being configured to execute the steps of the cell concentration counting method according to any embodiment of this disclosure based on the instructions stored in the memory.

[0007] This disclosure also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the cell concentration statistics method described in any embodiment of this disclosure.

[0008] This disclosure also provides a computer program product including instructions that, when executed by a computer, perform a cell concentration statistics method as described in any embodiment of this disclosure.

[0009] This disclosure also provides a cell concentration statistics system, including a processing device and an image acquisition device, wherein: The processing device is configured to determine an effective measurement region for a cell container to be tested, divide the effective measurement region into multiple sub-regions, wherein the cell container to be tested includes a first encapsulation layer, a second encapsulation layer, and a solution cavity disposed between the first encapsulation layer and the second encapsulation layer, wherein a first positioning mark is provided on one side of the first encapsulation layer facing the solution cavity, and a second positioning mark is provided on one side of the second encapsulation layer facing the solution cavity; detect the number of cells in the image of each sub-region, and sum the number of cells in the images of multiple sub-regions to obtain the total number of cells in the effective measurement region; calculate the difference between the first image acquisition height and the second image acquisition height to obtain the original cavity thickness; multiply the original cavity thickness by a preset adjustment coefficient to obtain an adjusted cavity thickness; calculate the volume of the effective measurement region based on the adjusted cavity thickness; and calculate the cell concentration based on the total number of cells and the volume of the effective measurement region. The image acquisition device is configured to focus on each sub-region and acquire an image of each sub-region; focus on the first positioning mark to obtain the first image acquisition height; and focus on the second positioning mark to obtain the second image acquisition height.

[0010] The cell concentration statistics method, apparatus, and system of this disclosure, by determining the effective measurement area of ​​the cell container to be tested, dividing the effective measurement area into multiple sub-regions, and using an image acquisition device to focus on and acquire images of each sub-region, solves the problem of blurred cell images caused by the non-coincidence of the focal plane of the image acquisition device and the plane where the cell is located, effectively improving the accuracy of cell concentration statistics; by using a preset adjustment coefficient to adjust the thickness of the first original cavity, the final calculated cavity thickness is closer to the actual cavity thickness, thereby improving the accuracy of the volume calculation of the effective measurement area, and further improving the accuracy of cell concentration statistics.

[0011] Other features and advantages of this disclosure will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the disclosure. Other advantages of this disclosure may be realized and obtained by means of the methods described in the description and the accompanying drawings. Attached Figure Description

[0012] The accompanying drawings are used to provide an understanding of the technical solutions of this disclosure and form part of the specification. They are used together with the embodiments of this disclosure to explain the technical solutions of this disclosure and do not constitute a limitation on the technical solutions of this disclosure.

[0013] Figure 1A This is a schematic diagram illustrating the relative positions of an image acquisition device and a cell container to be tested, which is an exemplary embodiment of this disclosure.

[0014] Figure 1B This is a schematic diagram of the structure of a cell container to be tested, which is an exemplary embodiment of this disclosure.

[0015] Figure 1C for Figure 1B A schematic diagram of the cross-sectional structure along the AA direction.

[0016] Figure 2 This is a schematic flowchart of a cell concentration statistics method as an exemplary embodiment of the present disclosure.

[0017] Figure 3 This is a schematic diagram illustrating the calibration process of an effective measurement area, which is an exemplary embodiment of this disclosure.

[0018] Figure 4A This is a schematic diagram of a cell image without impurities, which is an exemplary embodiment of this disclosure.

[0019] Figure 4B This is a schematic diagram illustrating a process for focusing a sub-region, which is an exemplary embodiment of the present disclosure.

[0020] Figure 5A This is a schematic diagram of a cell image containing impurities, which is an exemplary embodiment of the present disclosure.

[0021] Figure 5B This is a schematic diagram illustrating another process for focusing a sub-region, which is an exemplary embodiment of this disclosure.

[0022] Figure 6 This is a schematic diagram of a cell concentration counting device as an exemplary embodiment of the present disclosure.

[0023] Figure 7 This is a schematic diagram of the structure of a cell concentration statistics system, which is an exemplary embodiment of the present disclosure. Detailed Implementation

[0024] This disclosure describes several embodiments, but these descriptions are exemplary and not limiting, and it will be apparent to those skilled in the art that many more embodiments and implementations are possible within the scope of the embodiments described herein. Although many possible combinations of features are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are also possible. Unless specifically limited, any feature or element of any embodiment may be used in combination with, or may replace, any feature or element of any other embodiment.

[0025] This disclosure includes and contemplates combinations of features and elements known to those skilled in the art. The embodiments, features, and elements disclosed in this disclosure may also be combined with any conventional features or elements to form a unique inventive scheme as defined by the claims. Any feature or element of any embodiment may also be combined with features or elements from other inventive schemes to form another unique inventive scheme as defined by the claims. Therefore, it should be understood that any feature shown and / or discussed in this disclosure may be implemented individually or in any suitable combination. Therefore, the embodiments are not limited except by the limitations imposed by the appended claims and their equivalents. Furthermore, various modifications and changes may be made within the scope of the appended claims.

[0026] Furthermore, in describing representative embodiments, the specification may have presented methods and / or processes as a specific sequence of steps. However, the method or process should not be limited to the specific order of steps described herein, to the extent that the method or process does not depend on the specific order of steps described herein. As will be understood by those skilled in the art, other sequences of steps are also possible. Therefore, the specific order of steps set forth in the specification should not be construed as a limitation of the claims. Moreover, the claims relating to the method and / or process should not be limited to the steps performed in the order written, and those skilled in the art will readily understand that these orders can be varied and still remain within the spirit and scope of the embodiments disclosed herein.

[0027] This disclosure provides a method for statistical analysis of cell concentration, such as... Figures 1A to 1C As shown, the cell container to be tested includes a first encapsulation layer, a second encapsulation layer, and a solution cavity disposed between the first and second encapsulation layers. A first positioning mark is provided on the side of the first encapsulation layer facing the solution cavity, and a second positioning mark is provided on the side of the second encapsulation layer facing the solution cavity. Figure 2 As shown, the cell concentration statistical method includes: Step 201: Determine the effective measurement area of ​​the cell container (solution chamber) to be tested, divide the effective measurement area into multiple sub-regions, focus on each sub-region using an image acquisition device and acquire an image of each sub-region; Step 202: Detect the number of cells in the image of each sub-region, and sum the number of cells in the images of multiple sub-regions to obtain the total number of cells in the effective measurement area; Step 203: Focus the first positioning mark using the image acquisition device to obtain the first image acquisition height; focus the second positioning mark using the image acquisition device to obtain the second image acquisition height; calculate the difference between the first image acquisition height and the second image acquisition height to obtain the first original cavity thickness; multiply the first original cavity thickness by a preset adjustment coefficient to obtain the adjustment cavity thickness; calculate the volume of the effective measurement area based on the adjustment cavity thickness. Step 204: Calculate the cell concentration based on the total number and volume of cells in the effective measurement area.

[0028] Due to the surface tension of the cell staining solvent, cells near the cavity edge tend to aggregate towards the cavity edge after the solvent is injected. The cell concentration statistics method provided in this disclosure improves the accuracy of cell concentration statistics by determining the effective measurement area of ​​the solution cavity and avoiding the densely overlapping cell edges.

[0029] Due to manufacturing tolerances, machining precision, and assembly errors, the relative positions of the cell container on the stage and the central axis of the image acquisition device may no longer be perpendicular, resulting in a certain tilt angle. Consequently, the focal plane of the image acquisition device may no longer coincide with the plane where the cell is located, leading to relative displacement. Furthermore, because cells are small, an image acquisition device with a small depth of field (such as a high-magnification microscope) is required for image acquisition. However, even a small relative displacement between the focal plane of the image acquisition device and the plane where the cell is located can cause blurry images when the depth of field is small. The cell concentration statistics method provided in this disclosure solves the problem of blurry cell images caused by the misalignment of the focal plane of the image acquisition device with the plane where the cell is located by dividing the effective measurement area into multiple sub-regions, focusing on each sub-region, and acquiring an image for each sub-region.

[0030] The materials of the first and second encapsulation layers are not limited in this disclosure. For example, the first encapsulation layer may be composed of at least one of a cover plate, an inorganic film layer, or an organic film layer; the second encapsulation layer may be composed of at least one of a cover plate, an inorganic film layer, or an organic film layer.

[0031] like Figure 1C As shown, the entire cell container consists of three layers: the top layer is the first encapsulation layer (usually made of glass), the middle layer is adhesive, and the bottom layer is the second encapsulation layer (also usually made of glass). During the manufacturing process, when the middle layer is bonded to the top and bottom encapsulation layers, the thickness of the adhesive varies due to differences in adhesive strength, resulting in variations in the thickness of the cavity and ultimately causing errors in the calculation of cell concentration. To reduce the calculation errors caused by variations in cavity thickness, it is necessary to calculate the thickness of the solution cavity in each cell container to obtain the actual thickness of the solution cavity.

[0032] In this embodiment of the present disclosure, a first positioning mark is etched on one side of the first encapsulation layer facing the solution cavity (i.e., the lower surface of the first encapsulation layer), and a second positioning mark is etched on one side of the second encapsulation layer facing the solution cavity (i.e., the upper surface of the second encapsulation layer). The first positioning mark and the second positioning mark are aligned vertically (i.e., in the vertical direction). Figure 1A The first and second positioning marks do not completely overlap in the Z direction (i.e., the first and second positioning marks have non-overlapping areas in the vertical direction), which facilitates subsequent focusing and positioning of the first and second positioning marks separately. In some examples, the first and second positioning marks are staggered in the vertical direction.

[0033] For example, such as Figure 1BAs shown, both the first and second positioning marks are cross-shaped; however, this disclosure does not limit this, and the shapes of the first and second positioning marks can be set as needed. Next, the image acquisition device is moved to the initial focus positions corresponding to the two positioning marks, and the two positioning marks are focused on respectively. After focusing, two corresponding image acquisition height values ​​are obtained. and ,in, The image acquisition height value is obtained after focusing on the first positioning marker. This refers to the image acquisition height value obtained after focusing on the second positioning marker. Theoretically... and The difference between the two is the thickness of the solution cavity, denoted as the first original cavity thickness. However, in some cases (e.g., when the first encapsulation layer is made of glass, since the refractive index of glass is greater than 1), there is a certain error between the initial cavity thickness obtained by focusing and photographing the two positioning marks and the actual cavity thickness. Therefore, embodiments of this disclosure use an adjustment coefficient. The initial cavity thickness h obtained from focusing is adjusted to obtain the final cavity thickness (adjusting the cavity thickness). , recorded as The embodiments disclosed herein adjust the thickness of the first original cavity by using a preset adjustment coefficient, so that the final calculated cavity thickness is closer to the actual cavity thickness, thereby further improving the accuracy of cell concentration statistics.

[0034] In this embodiment, the effective measurement area does not include the edge region of the solution cavity or the region within a preset first distance threshold from the edge region. The first distance threshold can be from 3% to 10% of the solution cavity size. For example, assume the solution cavity is... Figures 1A to 1C The cuboid structure is defined with a first direction X as the length direction, a second direction Y as the width direction, and a third direction Z as the thickness direction (or vertical direction). In the first direction X (length direction), a first distance threshold can be 5% of the dimension (i.e., length) of the solution cavity in the first direction X. Similarly, in the second direction Y (width direction), the first distance threshold can be 5% of the dimension (i.e., width) of the solution cavity in the second direction. However, this disclosure does not impose any limitations on this. This allows the effective measurement area to avoid the cavity edge region where cells are densely overlapping, thereby improving the accuracy of cell concentration statistics.

[0035] Calculating cell concentration requires the volume of the solution cavity, and accurately measuring the cavity thickness is crucial. This embodiment obtains an adjustment coefficient by focusing twice on a first and second positioning marker using an image acquisition device and by measuring the total thickness of a first calibrated cell container with the same structure. This adjustment coefficient can be used to adjust the calculated initial cavity thickness of the cell container to be measured, and the adjusted cavity thickness can be used to calculate the volume of a sub-region or the effective measurement region.

[0036] In this embodiment of the disclosure, the execution order of steps 202 and 203 can be interchanged, and this disclosure does not impose any restrictions on this.

[0037] In this embodiment of the disclosure, the image acquisition device can be a high-magnification microscope with a photography function; however, this disclosure does not limit it.

[0038] In some exemplary embodiments, in step 203, the preset adjustment coefficient can be determined by the following method: A first calibration cell container is obtained. The structure of the first calibration cell container is the same as that of the cell container to be tested. The material of the first encapsulation layer of the first calibration cell container is the same as that of the first encapsulation layer of the cell container to be tested. The staining solution of the first calibration cell container is the same as that of the cell container to be tested. The first positioning mark in the first calibrated cell container is focused by the image acquisition device to obtain the third image acquisition height; the second positioning mark in the first calibrated cell container is focused by the image acquisition device to obtain the fourth image acquisition height; the difference between the third image acquisition height and the fourth image acquisition height is calculated to obtain the second original cavity thickness. The total thickness of the first calibrated cell container is measured by an instrument, and the thickness of the first encapsulation layer and the thickness of the second encapsulation layer of the first calibrated cell container are subtracted from the total thickness of the first calibrated cell container to obtain the actual cavity thickness of the first calibrated cell container. The adjustment coefficient is obtained by calculating the quotient of the actual cavity thickness of the first calibrated cell container and the original cavity thickness of the second container.

[0039] Since the magnitude of the refractive index is only related to the material of the medium, in this embodiment of the disclosure, as long as the material of the first encapsulation layer of the cell container to be tested is the same as the material of the first encapsulation layer of the first calibration cell container (the size of the cell container to be tested and the size of the first calibration cell container may be different), the adjustment coefficient obtained in advance based on the first calibration cell container can be directly used when calculating the cell concentration of the cell container to be tested.

[0040] For example, the adjustment factor is determined based on the first calibrated cell container. The method is as follows: Obtain a first calibrated cell container. Focus the first and second positioning marks within the first calibrated cell container using an image acquisition device to obtain a third and fourth image acquisition height. Calculate the difference between the third and fourth image acquisition heights to obtain the original cavity thickness of the first calibrated cell container (denoted as the second original cavity thickness). Measure the total thickness of the first calibrated cell container using a precision instrument. Subtract the thicknesses of the first encapsulation layer (e.g., the upper glass cover) and the second encapsulation layer (e.g., the lower glass cover) from this total thickness to obtain the actual cavity thickness of the first calibrated cell container, denoted as... Calculate the adjustment factor according to the following formula. .

[0041] The cell concentration statistics method of this disclosure involves focusing twice on two positioning markers of the cell container to be tested, measuring the thickness of the first original cavity of the cell container to be tested, and then multiplying the thickness of the first original cavity of the cell container to be tested by an adjustment factor. The adjusted cavity thickness (i.e., the final cavity thickness) of the cell container to be tested is obtained.

[0042] If the effective measurement area of ​​the cell image corresponds to the actual length and width of the cell container being measured, then... and The thickness of the first original cavity, as determined by the focusing method, is The volume of the solution corresponding to the effective measurement area is: This embodiment improves the accuracy of calculating the volume of the effective measurement area by adjusting the thickness of the first original cavity, thereby improving the accuracy of cell concentration statistics for the cell container under test.

[0043] In some exemplary embodiments, in step 201, determining the effective measurement region of the cell container to be tested includes: Obtain a second calibration cell container, the size of which is the same as the size of the cell container to be tested, and the cell concentration of the second calibration cell container is known. Determine the cell concentration in multiple candidate measurement regions, where the size of each candidate measurement region is less than or equal to the size of the solution chamber of the second calibration cell container; Select the candidate measurement region corresponding to the cell concentration closest to the known cell concentration of the second calibrated cell container, which is the effective measurement region for the solution chamber of the same size.

[0044] Due to the surface tension of the cell staining solvent, cells near the cavity edge tend to aggregate towards the edge after the solvent is injected. Therefore, when photographing cells within the cavity, it is necessary to select a central, effective measurement area. For example, the effective measurement area can be calibrated using the following method: Select a known particle concentration (let the concentration be ). The solution is injected into the cavity, and after the particles settle for a period of time, multiple candidate measurement areas are selected. The solutions in the multiple candidate measurement areas are photographed and their concentrations are calculated (using the cell concentration statistical method of the present disclosure embodiment). The different solution concentrations corresponding to the multiple candidate measurement areas are obtained. All calculated concentrations are compared with the known particle concentration N, and the candidate measurement area with the concentration closest to the known particle concentration N is selected. This selected candidate measurement area is used as the effective measurement area when actually measuring the cell solution concentration.

[0045] The embodiments disclosed herein calibrate the size of the effective measurement area using a pre-set calibration method, thereby further improving the accuracy of cell concentration statistics in the effective measurement area.

[0046] In some other exemplary embodiments, step 201, determining the effective measurement region of the cell container to be tested, includes: Obtain a second calibration cell container. The size of the solution chamber of the second calibration cell container is the same as that of the cell container to be tested, and the cell concentration of the second calibration cell container is known. Select an initial measurement area for the solution chamber of the second calibration cell container. Determine the cell concentration in the measurement region and calculate the error between the cell concentration in the measurement region and the cell concentration in the second calibrated cell container; The measurement area is magnified in the first direction (and / or the second direction) by a preset magnification ratio. It is then checked whether the size of the measurement area in the first direction (and / or the second direction) is less than or equal to the size of the solution cavity in the first direction (and / or the second direction). If the size of the measurement area in the first direction (and / or the second direction) is less than or equal to the size of the solution cavity in the first direction (and / or the second direction), the process returns to the step of determining the cell concentration of the measurement area and continues. Determine the minimum value among the calculated errors, and use the measurement area corresponding to the minimum value as the effective measurement area of ​​the solution cavity of the same size.

[0047] For example, the center of the initial measurement region coincides with or nearly coincides with the center of the solution cavity (i.e., the distance between the center of the initial measurement region and the center of the solution cavity is less than or equal to a preset second distance threshold), and the ratio of the size of the initial measurement region in the first direction to the size of the solution cavity in the first direction is equal to the ratio of the size of the initial measurement region in the second direction to the size of the solution cavity in the second direction, wherein the first direction intersects with the second direction.

[0048] In this embodiment of the disclosure, the initial measurement region can be a relatively small area. In subsequent loops, the size of the measurement region in the first direction (and / or the second direction) is gradually increased by a preset magnification ratio to find the measurement region with the concentration closest to the cell concentration of the second calibrated cell container as the effective measurement region. In other examples, the initial measurement region can be a relatively large area. In subsequent loops, the size of the measurement region in the first direction (and / or the second direction) is gradually decreased by a preset reduction ratio to find the measurement region with the concentration closest to the cell concentration of the second calibrated cell container as the effective measurement region.

[0049] In this embodiment of the disclosure, when the shape of the measuring area is rectangular, the dimension of the measuring area in the first direction can be referred to as the length, and the dimension of the measuring area in the second direction can be referred to as the width. However, this disclosure does not limit this, and the shape of the measuring area can be set as needed.

[0050] In this embodiment of the present disclosure, the error between the calculated cell concentration in the measurement area and the cell concentration in the second calibrated cell container can also be replaced by the difference between the cell concentration in the measurement area and the cell concentration in the second calibrated cell container, and the present disclosure does not limit this.

[0051] For example, taking a rectangular measurement area as an example, assuming the initial length of the measurement area is... Width is The length of the entire solution cavity is Width is ,but However, this disclosure does not limit this. In embodiments of this disclosure, by aligning or nearly aligning the center of the initial measurement region with the center of the solution cavity, and by setting the ratio of the length of each initial measurement region to the length of the solution cavity of the second calibration cell container to be equal to the ratio of the width of each initial measurement region to the width of the solution cavity of the second calibration cell container, the effective measurement region can be determined by starting from the initial measurement region, enlarging the measurement region according to a preset magnification ratio, and finding the measurement region whose concentration is closest to the cell concentration of the second calibration cell container from among multiple measurement regions as the effective measurement region.

[0052] For example, such as Figure 3 As shown, the effective measurement area can be calibrated using the following method: Select a known particle concentration (let the concentration be ). The solution is injected into the cavity, and after waiting for the particles to settle for a period of time, an initial rectangular frame is selected with the center of the cavity as the center point. Let's assume the initial rectangular frame is... The corresponding length and width are denoted as follows: and The solution inside the rectangle is photographed and its concentration is calculated (using the cell concentration statistics method of this disclosure). Assume the initial concentration calculated for the rectangle is... ,calculate Error between known particle concentration Next, at the preset magnification ratio... 1 ( (A real number greater than 1) The rectangle is expanded sequentially, and the steps of taking pictures, calculating the concentration and the error between the concentration and the known particle concentration are repeated. The minimum value e among the multiple errors is taken, and the rectangle corresponding to the minimum value e is taken as the rectangle whose concentration is closest to the known particle concentration N. The size of this rectangle is taken as the size of the effective measurement area when actually measuring the cell solution concentration.

[0053] In some embodiments, the above calibration steps can be repeated multiple times, and the average value of the rectangular frame size closest to the concentration N in each calibration can be taken as the effective measurement area when actually measuring the cell solution concentration.

[0054] This embodiment of the invention measures the concentration of a solution with known particle concentrations in different sized measurement regions and compares the error magnitudes to determine the final effective measurement region size, thus avoiding the problem of low accuracy in cell concentration statistics caused by dense overlap of cells at the cavity edge.

[0055] In some exemplary embodiments, in step 201, the effective measurement area is divided into multiple sub-regions, and an image acquisition device focuses on each sub-region and acquires an image of each sub-region, including: The effective measurement area is divided into multiple first sub-regions, and each first sub-region is divided into multiple second sub-regions; The image acquisition device focuses on each first sub-region according to a preset first traversal order, and after each focusing, the image acquisition device acquires images of each second sub-region contained in the first sub-region that was focused, according to a preset second traversal order.

[0056] In this embodiment, the dimensions of the plurality of first sub-regions may be the same or different; the dimensions of the plurality of second sub-regions may be the same or different. This disclosure does not impose any limitations on this.

[0057] In some exemplary implementations, the number of first sub-regions is n*m, and the number of second sub-regions contained in each first sub-region is i*j, where n, m, i, and j are all natural numbers greater than 1.

[0058] For example, such as Figure 1A As shown, the entire solution cavity is evenly divided into 4*4=16 first sub-regions, and each first sub-region is evenly divided into 2*2 second sub-regions.

[0059] In some exemplary embodiments, the preset first traversal order can be from left to right or from top to bottom; the preset second traversal order can be from left to right or from top to bottom. However, this disclosure does not limit this. The first traversal order of multiple first sub-regions and the second traversal order of the second sub-regions within each first sub-region can be set as needed. For example, the preset first traversal order can adopt a serpentine traversal method, that is, the first row is from left to right, the second row is from right to left, and so on (odd rows from left to right, even rows from right to left). The preset second traversal order can also adopt a serpentine traversal method, that is, the first row is from left to right, the second row is from right to left, and so on (odd rows from left to right, even rows from right to left).

[0060] Due to factors such as container manufacturing tolerances, machining precision, and assembly errors, the container will tilt in a certain direction after being placed on the stage. The container surface and the central axis of the image acquisition device will no longer be perpendicular, but will have a certain deviation angle. As the relative displacement between the image acquisition device and the container increases, the deviation between the focal plane of the image acquisition device and the plane where the cell is located will increase, resulting in blurred cell images and affecting subsequent image processing, cell counting, and concentration calculation.

[0061] In this embodiment of the present disclosure, the entire solution cavity is divided into multiple first sub-regions, and each first sub-region is further divided into multiple second sub-regions. When determining the solution concentration, the first sub-region is focused first, and then each second sub-region is photographed. This method of focusing and photographing in different regions can effectively avoid the problem of blurred cell images caused by the deviation between the focal plane of the image acquisition device and the plane where the cell is located.

[0062] In practical use, the size and number of the first sub-regions can be determined through multiple experiments. Too many first sub-regions will result in too many focusing attempts, increasing measurement time and affecting measurement efficiency; too few first sub-regions may result in some blurry images within the same first sub-region. Therefore, when determining the number and size of the first sub-regions, it is important to balance the image quality and measurement efficiency as much as possible.

[0063] In some exemplary embodiments, in step 201, focusing on each sub-region (first sub-region) using the image acquisition device includes: The image acquisition device is moved to multiple height positions above the center of each sub-region (first sub-region), and images are acquired at each height position; Calculate the image sharpness at multiple height positions; Use the height position corresponding to the image with the highest resolution as the final focus position.

[0064] In this embodiment of the disclosure, the multiple height positions can be preset height positions, and the distances between each height position can be equal or unequal, which is not limited in this disclosure.

[0065] In a blurry image, the outlines of objects are not clear, and the gray-level changes at the edges of the outlines are not strong, resulting in a weak sense of depth. In contrast, in a clear image, the gray-level changes at the edges of the object's outlines are obvious, resulting in a strong sense of depth. Therefore, in this embodiment of the disclosure, image gradient is used to measure the rate of change of image gray-level, i.e., to evaluate the image's sharpness.

[0066] In some other exemplary embodiments, in step 201, focusing is performed on each sub-region (first sub-region) by the image acquisition device, including: The image acquisition device is moved to an initial height position above the center of each sub-region (the first sub-region), and images are acquired and their sharpness is calculated at the initial height position. Starting from the initial height position, the image acquisition device is moved upwards every third distance interval. After each movement, an image is acquired through the image acquisition device, and the clarity of each acquired image is detected to see if it decreases. When a decrease in the sharpness of the acquired image is detected, the height position of the image acquisition device at the start of this movement is taken as the final focus position.

[0067] In this embodiment of the disclosure, multiple height positions are determined by an initial height position and a preset third distance interval.

[0068] like Figure 4A As shown, for a normal image without impurities, the solution contains only normally stained cells. Figure 4B As shown, the process of focusing on each sub-region includes: moving the image acquisition device to an initial height position directly above the sub-region, wherein the initial height position can be a position relatively close to the cell container (i.e., a slightly lower position), however, this disclosure does not limit this; acquiring an image at the initial height position and calculating the image sharpness; then moving the image acquisition device upwards in the vertical direction at certain distance intervals, acquiring one image each time it moves, simultaneously calculating the image sharpness, and recording the corresponding height position; when a decrease in sharpness occurs, the sharpness of the previous image is taken as the maximum sharpness, denoted as . The height position of the image acquisition device corresponding to the maximum resolution image. This serves as the final focus point.

[0069] In some exemplary embodiments, in step 201, each sub-region (first sub-region) is focused, specifically: one or more regions of interest are focused, wherein the object outline shape within the region of interest includes only a preset first shape and does not include shapes other than the preset first shape.

[0070] In this embodiment of the present disclosure, the preset first shape includes at least one of the following: a circle or an ellipse. However, the present disclosure is not limited thereto. The preset first shape can be set as needed.

[0071] In some exemplary embodiments, the region of interest is determined by the following method: Images are acquired for each sub-region (the first sub-region), and the acquired images are binarized and edge detected to obtain multiple contour shapes; Identify the outline of one or more preset first shapes from multiple outline shapes, and record the outline center and size of each first shape's outline; Generate a region of interest, which includes the area covered by the outline of at least one first shape.

[0072] like Figure 5A As shown, during the focusing process, the acquired image may contain large impurities, and these impurities may be at different heights from the cells. If the entire image is focused in this case, the focusing plane may be positioned at the height of the impurities, causing blurring of the cells in the acquired image and thus affecting cell counts. This embodiment solves the problem of the focusing plane potentially being positioned at the height of the impurities by focusing on the region of interest.

[0073] like Figure 5B As shown, taking a circle as an example of a preset first shape, the region of interest in this embodiment is determined by the following method: Before focusing, a cell image is acquired; the cell image is binarized to convert the acquired cell image (grayscale image) into a binary image; edge extraction is performed on the binary image to extract the edge contours in the image; then, a first feature detection algorithm is used to identify the circular contours, and the pixel coordinates and diameter of the center of these contours in the image are recorded, denoted as […]. and Then take a certain quantity The circular outline, with Centered on, with Take a square region with side length , where 2 is the preset magnification factor. By expanding the circular area into a square area, the circular outline can be completely included in order to calculate the sharpness; the square area is used as the generated region of interest.

[0074] In this embodiment of the disclosure, the first feature detection algorithm can be a circular or near-circular detection method. For example, the circular or near-circular detection method can be a circular or near-circular detection method based on Hough transform. However, this disclosure does not limit it. Since the first feature detection algorithm is only used to determine the region of interest, the first feature detection algorithm only needs to be able to roughly detect circles or ellipses.

[0075] In this embodiment, after generating the region of interest, the region of interest can be focused following the steps described above for focusing a normal image. However, instead of focusing the entire image (i.e., calculating sharpness), the selected contour region (i.e., the region of interest) is focused (i.e., its sharpness is calculated).

[0076] In some exemplary embodiments, generating a region of interest includes: Generate one or more rectangular regions, each of which covers at least the outline of a preset first shape, and use the rectangular regions as regions of interest.

[0077] In this embodiment of the disclosure, the rectangular region can be a square structure or a rectangular structure. For example, when the preset first shape is a circle, the rectangular region is a square structure; when the preset first shape is an ellipse, the rectangular region is a rectangular structure.

[0078] In this embodiment of the present disclosure, in step 202, the number of cells in the image of each sub-region can be detected using a second feature detection algorithm; however, the present disclosure does not limit this.

[0079] For example, for a single cell type, the second feature detection algorithm can employ a circular or near-circular detection method based on Hough transform; however, for multiple cells with similar shapes but different types, the second feature detection algorithm can employ neural network-related feature detection algorithms, such as YOLO, R-CNN series, and other object detection algorithms, to handle the detection of cells with similar shapes but different types in the same image. However, this disclosure does not limit this; the specific implementation of the second feature detection algorithm can be set as needed. For example, for a single cell type, the second feature detection algorithm can also employ neural network-related feature detection algorithms, etc.

[0080] In this embodiment of the disclosure, step 204, calculating the cell concentration based on the total number and volume of cells in the effective measurement area, includes: Calculate the quotient of the total number of cells in the effective measurement area to the volume, and use the calculated quotient as the cell concentration.

[0081] In summary, when using the cell concentration statistical method of this disclosure to statistically analyze the concentration of the cell container to be tested, the effective measurement area of ​​the cavity in the container is first selected, and the effective measurement area is divided into n×m first sub-regions, denoted as area1. Then, each area1 is divided into i×j second sub-regions, denoted as area2. The image acquisition device starts measuring from area 1 in the upper left corner. For each area 1, it can measure area 2 in sequence from left to right and from top to bottom. Each area 2 corresponds to acquiring at least one cell image. The traversal of area 1 can also be in the order from left to right and from top to bottom. Before each measurement of area 1, the center of area 1 must be focused. After focusing, the image acquisition device is moved to area 2 in the upper left corner of area 1. After traversing and taking pictures, a total of n×m×i×j images are acquired. After each image is taken, the number of cells in the image is detected by a preset second feature detection algorithm. The number of cells in all images is added together to get the total number of cells, sum. The solution volume corresponding to each area 2 is denoted as v. The calculated cell concentration is sum / (n×m×i×j×v).

[0082] This disclosure also provides a cell concentration counting device, including a memory; and a processor connected to the memory, the memory being used to store instructions, the processor being configured to perform the steps of the cell concentration counting method as described in any embodiment of this disclosure based on the instructions stored in the memory.

[0083] like Figure 6 As shown, in one example, the cell concentration counting device may include: a processor 610, a memory 620, a bus system 630, and a transceiver 640. The processor 610, memory 620, and transceiver 640 are connected via the bus system 630. The memory 620 stores instructions, and the processor 610 executes the instructions stored in the memory 620 to control the transceiver 640 to transmit and receive signals. Specifically, the transceiver 640 acquires images of each sub-region, a first image acquisition height, and a second image acquisition height. The processor 610 determines the effective measurement area of ​​the cell container to be measured, divides the effective measurement area into multiple sub-regions, detects the number of cells in the image of each sub-region, and sums the number of cells in the images of multiple sub-regions to obtain the total number of cells in the effective measurement area. The first original cavity thickness is multiplied by a preset adjustment coefficient to obtain the adjusted cavity thickness. The volume of the effective measurement area is calculated based on the adjusted cavity thickness. The cell concentration is calculated based on the total number of cells and the volume of the effective measurement area.

[0084] It should be understood that processor 610 can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0085] Memory 620 may include read-only memory and random access memory, and provides instructions and data to processor 610. A portion of memory 620 may also include non-volatile random access memory. For example, memory 620 may also store device type information.

[0086] In addition to a data bus, the bus system 630 may also include a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 6 The general labeled all buses as Bus System 630.

[0087] In implementation, the processing performed by the processing device can be accomplished through integrated logic circuits in the hardware of the processor 610 or through software instructions. That is, the method steps of this embodiment can be executed by a hardware processor, or by a combination of hardware and software modules within the processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other storage media. This storage medium is located in memory 620, and the processor 610 reads information from memory 620 and, in conjunction with its hardware, completes the steps of the aforementioned method. To avoid repetition, further details are omitted here.

[0088] This disclosure also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the cell concentration statistics method as described in any embodiment of this disclosure. The cell concentration statistics method driven by executing executable instructions is essentially the same as the cell concentration statistics method provided in the above embodiments of this disclosure, and will not be described in detail here.

[0089] In some possible implementations, various aspects of the cell concentration counting method provided in this disclosure may also be implemented as a program product comprising program code that, when run on a computer device, causes the computer device to perform the steps in the cell concentration counting method according to various exemplary embodiments of this disclosure as described above. For example, the computer device may execute the cell concentration counting method described in the embodiments of this disclosure.

[0090] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0091] It will be understood by those skilled in the art that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0092] Figure 7 This is a schematic diagram of the structure of a cell concentration statistics system provided as an exemplary embodiment of this disclosure. Figure 7 As shown in the embodiments of this disclosure, a cell concentration counting system is also provided, including an image acquisition device and a processing device, wherein: The processing device is configured to: determine the effective measurement area of ​​a cell container to be tested; divide the effective measurement area into multiple sub-regions; the cell container to be tested includes a first encapsulation layer, a second encapsulation layer, and a solution cavity disposed between the first and second encapsulation layers; a first positioning mark is set on the side of the first encapsulation layer facing the solution cavity, and a second positioning mark is set on the side of the second encapsulation layer facing the solution cavity; detect the number of cells in the image of each sub-region, and sum the number of cells in the images of multiple sub-regions to obtain the total number of cells in the effective measurement area; calculate the difference between the first image acquisition height and the second image acquisition height to obtain the original cavity thickness; multiply the first original cavity thickness by a preset adjustment coefficient to obtain the adjusted cavity thickness; calculate the volume of the effective measurement area based on the adjusted cavity thickness; and calculate the cell concentration based on the total number of cells and the volume of the effective measurement area. The image acquisition device is configured to focus on each sub-region and acquire an image of each sub-region; focus on a first positioning marker to obtain a first image acquisition height; and focus on a second positioning marker to obtain a second image acquisition height.

[0093] Since the principle behind this cell concentration statistics system is similar to that of the aforementioned cell concentration statistics method, the implementation of this cell concentration statistics system can be found in the implementation of the aforementioned cell concentration statistics method, and the repetitions will not be repeated.

[0094] It should be noted that the above embodiments or implementation methods are merely exemplary and not restrictive. Therefore, this disclosure is not limited to the content specifically shown and described herein. Various modifications, substitutions, or omissions can be made to the form and details of the implementations without departing from the scope of this disclosure.

Claims

1. A method of cell concentration statistics, comprising: include: The effective measurement area of ​​the cell container to be tested is determined, and the effective measurement area is divided into multiple sub-regions. Each sub-region is focused and an image is acquired by an image acquisition device. The cell container to be tested includes a first encapsulation layer, a second encapsulation layer, and a solution cavity disposed between the first encapsulation layer and the second encapsulation layer. A first positioning mark is provided on one side of the first encapsulation layer facing the solution cavity, and a second positioning mark is provided on one side of the second encapsulation layer facing the solution cavity. The number of cells in the image of each sub-region is detected, and the number of cells in the images of multiple sub-regions is summed to obtain the total number of cells in the effective measurement region; The first positioning mark is focused using the image acquisition device to obtain a first image acquisition height; the second positioning mark is focused using the image acquisition device to obtain a second image acquisition height; the difference between the first image acquisition height and the second image acquisition height is calculated to obtain a first original cavity thickness; the first original cavity thickness is multiplied by a preset adjustment coefficient to obtain an adjusted cavity thickness; the volume of the effective measurement area is calculated based on the adjusted cavity thickness. The cell concentration is calculated based on the total number and volume of cells in the effective measurement area.

2. The method of claim 1, wherein, The preset adjustment coefficient is determined by the following method: A first calibration cell container is obtained, the structure of the first calibration cell container is the same as the structure of the cell container to be tested, the material of the first encapsulation layer of the first calibration cell container is the same as the material of the first encapsulation layer of the cell container to be tested, and the staining solution of the first calibration cell container is the same as the staining solution of the cell container to be tested. The third image acquisition height is obtained by focusing the first positioning mark in the first calibrated cell container using the image acquisition device. The image acquisition device focuses on the second positioning mark in the first calibrated cell container to obtain the fourth image acquisition height; The difference between the third image acquisition height and the fourth image acquisition height is calculated to obtain the second original cavity thickness; The total thickness of the first calibrated cell container is measured by an instrument, and the thickness of the first encapsulation layer and the second encapsulation layer of the first calibrated cell container are subtracted from the total thickness of the first calibrated cell container to obtain the actual cavity thickness of the first calibrated cell container. The adjustment coefficient is the quotient obtained by dividing the actual cavity thickness of the first calibrated cell container by the original cavity thickness of the second container.

3. The method of claim 1, wherein, Determining the effective measurement region of the cell container to be tested includes: A second calibration cell container is obtained, wherein the size of the solution chamber of the second calibration cell container is the same as the size of the cell container to be tested, and the cell concentration of the second calibration cell container is known; The cell concentration of a plurality of candidate measurement regions is determined, wherein the size of each candidate measurement region is less than or equal to the size of the solution cavity of the second calibration cell container; Select the candidate measurement area corresponding to the cell concentration closest to that of the second calibrated cell container as the effective measurement area of ​​the solution cavity of the same size.

4. The method of claim 1, wherein, Determining the effective measurement region of the cell container to be tested includes: Obtain a second calibration cell container, the size of which is the same as the size of the cell container to be tested, and the cell concentration of the second calibration cell container is known; select an initial measurement area for the solution cavity of the second calibration cell container; Determine the cell concentration in the measurement region and calculate the error between the cell concentration in the measurement region and the cell concentration in the second calibrated cell container; The measurement area is magnified by a preset magnification ratio in the first and / or second directions. It is then detected whether the size of the measurement area in the first and / or second directions is less than or equal to the size of the solution cavity in the first and / or second directions. If the size of the measurement area in the first and / or second directions is less than or equal to the size of the solution cavity in the first and / or second directions, the process returns to the step of determining the cell concentration of the measurement area and continues. The minimum value among the calculated errors is determined, and the measurement area corresponding to the minimum value is taken as the effective measurement area of ​​the solution cavity of the same size.

5. The method according to claim 4, characterized in that, The center of the initial measurement region coincides with the center of the solution cavity; the ratio of the size of the initial measurement region in the first direction to the size of the solution cavity of the second calibration cell container in the first direction is equal to the ratio of the size of the initial measurement region in the second direction to the size of the solution cavity of the second calibration cell container in the second direction, wherein the first direction intersects the second direction.

6. The method according to claim 1, characterized in that, The step of dividing the effective measurement area into multiple sub-regions, focusing on each sub-region using an image acquisition device, and acquiring an image of each sub-region includes: The effective measurement area is divided into multiple first sub-regions, and each first sub-region is divided into multiple second sub-regions; The image acquisition device focuses on each of the first sub-regions according to a preset first traversal order, and after each focusing, the image acquisition device acquires images of each of the second sub-regions contained in the first sub-region that was focused, according to a preset second traversal order.

7. The method according to claim 1, characterized in that, The step of focusing each sub-region using an image acquisition device includes: The image acquisition device is moved to multiple height positions above the center of each sub-region, and images are acquired at each height position using the image acquisition device. Calculate the image sharpness corresponding to each of the stated height positions; Use the height position corresponding to the image with the highest resolution as the final focus position.

8. The method according to claim 1, characterized in that, The step of focusing each sub-region using an image acquisition device includes: The image acquisition device is moved to an initial height position above the center of each sub-region, and images are acquired at the initial height position using the image acquisition device, and the image sharpness is calculated. Starting from the initial height position, the image acquisition device moves upward once at preset distance intervals. After each movement, the image acquisition device acquires an image and detects whether the clarity of the acquired image decreases. When the image sharpness begins to decrease, the height position of the image acquisition device at the start of the current movement is taken as the final focus position.

9. The method according to claim 1, characterized in that, The step of focusing on each of the sub-regions specifically involves focusing on one or more regions of interest, wherein the object outline shape within the region of interest includes a preset first shape and does not include shapes other than the preset first shape.

10. The method according to claim 9, characterized in that, The preset first shape includes at least one of the following: circle or ellipse.

11. The method according to claim 9, characterized in that, The region of interest is determined by the following method: Images are acquired for each of the sub-regions, and the acquired images are binarized and edge detected to obtain multiple contour shapes; Identify one or more of the preset first shapes from the plurality of said contour shapes, and record the contour center and size of each of the preset first shapes; The region of interest is generated, which includes the area covered by the preset first shape.

12. The method according to claim 11, characterized in that, Generating the region of interest includes: One or more rectangular regions are generated, each rectangular region covering at least the outline of a preset first shape, and the rectangular regions are used as the regions of interest.

13. A cell concentration counting device, characterized in that, The method includes a memory; and a processor connected to the memory, the memory being used to store instructions, the processor being configured to perform the steps of the cell concentration statistics method as described in any one of claims 1 to 12 based on the instructions stored in the memory.

14. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the cell concentration statistical method as described in any one of claims 1 to 12.

15. A computer program product, characterized in that, The instruction includes instructions that, when the computer program product is executed by a computer, perform the cell concentration statistics method as described in any one of claims 1 to 12.

16. A cell concentration counting system, characterized in that, It includes a processing unit and an image acquisition unit, wherein: The processing device is configured to determine the effective measurement area of ​​a cell container to be tested, divide the effective measurement area into multiple sub-regions, wherein the cell container to be tested includes a first encapsulation layer, a second encapsulation layer, and a solution cavity disposed between the first encapsulation layer and the second encapsulation layer, wherein a first positioning mark is provided on one side of the first encapsulation layer facing the solution cavity, and a second positioning mark is provided on one side of the second encapsulation layer facing the solution cavity; detect the number of cells in the image of each sub-region, and sum the number of cells in the images of multiple sub-regions to obtain the total number of cells in the effective measurement area; calculate the difference between the first image acquisition height and the second image acquisition height to obtain the original cavity thickness; multiply the original cavity thickness by a preset adjustment coefficient to obtain the adjusted cavity thickness; calculate the volume of the effective measurement area based on the adjusted cavity thickness; and calculate the cell concentration based on the total number of cells and the volume of the effective measurement area. The image acquisition device is configured to focus on each sub-region and acquire an image of each sub-region; focus on the first positioning mark to obtain the first image acquisition height; and focus on the second positioning mark to obtain the second image acquisition height.

Images