WO2022100517A1 - 细胞分析方法和系统及定量方法和系统 - Google Patents

细胞分析方法和系统及定量方法和系统 Download PDF

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WO2022100517A1
WO2022100517A1 PCT/CN2021/128836 CN2021128836W WO2022100517A1 WO 2022100517 A1 WO2022100517 A1 WO 2022100517A1 CN 2021128836 W CN2021128836 W CN 2021128836W WO 2022100517 A1 WO2022100517 A1 WO 2022100517A1
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cell
image
cells
microscopic image
area
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PCT/CN2021/128836
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French (fr)
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王志平
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深圳安侣医学科技有限公司
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/02—Investigating particle size or size distribution
    • G01N15/0205—Investigating particle size or size distribution by optical means
    • G01N15/0227—Investigating particle size or size distribution by optical means using imaging; using holography
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N1/00—Sampling; Preparing specimens for investigation
    • G01N1/28—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q
    • G01N1/30—Staining; Impregnating ; Fixation; Dehydration; Multistep processes for preparing samples of tissue, cell or nucleic acid material and the like for analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/02—Investigating particle size or size distribution
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/1012—Calibrating particle analysers; References therefor
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/58—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving labelled substances
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/02—Investigating particle size or size distribution
    • G01N2015/0288—Sorting the particles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N2015/1006—Investigating individual particles for cytology
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/1012—Calibrating particle analysers; References therefor
    • G01N2015/1014—Constitution of reference particles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N2015/1029—Particle size
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N2015/103—Particle shape

Definitions

  • the present application belongs to the field of cell analysis methods and systems; in particular, it relates to a method and system for cell analysis based on microscopic images obtained after imaging a cell suspension sample.
  • FIG. 3 it is a schematic diagram of the production process of a blood smear in the prior art. It can be seen from the figure that it includes the steps of making the blood smear and the step of staining the blood smear.
  • the steps of making the blood smear include four small steps: respectively, step 1.1: drop the blood sample onto the glass slide; step 1.2: take another glass slide, tilt it at an angle of 30° to 45°, and move it to the other side at a constant speed. Push on one side; Step 1.3: The blood film is evenly coated, and the "flame" shape is a qualified smear; Step 1.4: Wait for the blood film to dry and prepare for staining.
  • the steps of smear staining include five small steps: respectively, step 2.1: mark the blood smear with a pencil, place the blood smear on the staining rack, and draw the crayon line to prevent liquid spillage; step 2.2: after the blood smear is naturally dried , drip 1-2 drops of dye solution to cover the blood piece, and dye for about 1 minute; Step 2.3: Add a little more volume (such as 2-4 drops) of buffer solution, blow it with the dye solution with ear washing ball, and dye it for about 5 Minute; Step 2.4: Shake the slide slowly, then rinse the stain solution from one side of the glass slide with a thin stream of tap water (note that you need to pour the stain solution first and then rinse it) for about 1 minute; Step 2.5: After rinsing is terminated, the blood slices can be dried naturally or blotted with filter paper, and can be used for microscopic examination.
  • the number of cells on the smear for microscopy is observed and counted manually under a microscope, and the observation efficiency is extremely low. Not only in the scene of brightfield microscopy, but also in some scenes of fluorescence imaging microscopy, there are similar problems in brightfield detection, and both observation and counting are inefficient. In addition, during the observation process, the magnification of each imaging image may be different, and the cell classification and counting can only be performed based on experience; the cell size in the image cannot be accurately calculated.
  • the counting logic is to carry out cell counting by introducing a counting bearing surface net that can carry independent cells; the bearing surface net corresponds to the size of a single compartment.
  • Cells can be well-carried for display and used for cell identification and counting. Due to the wide variety of cells, different cells need to be designed to accommodate different cell sizes.
  • the accuracy of its counting depends more on the structure and processing accuracy of the counting plate, that is, the bearing surface net that forms the observation layer, especially the volume of the cell tiling area or distribution area. When the processing accuracy is not enough, the error is very large, and accordingly Errors in cell identification and classification counts are also greatly increased.
  • the technical problem to be solved by the present application is to avoid the above-mentioned shortcomings of the prior art, and to propose a simple and efficient method for cell analysis.
  • the reference particles can be used for cell analysis, which improves the efficiency of cell analysis, especially in cell analysis. It is the comprehensive efficiency of cell count and cell concentration calculation, and improves the accuracy of calculation, and can reduce the influence of systematic errors in cell analysis.
  • the technical solution of the present application to solve the above problems is a method for obtaining the actual size of cells in a cell suspension sample, based on a microscopic image;
  • the microscopic image is that cells and reference particles in the cell suspension sample settle on the bearing surface of the carrier At least one microscopic image of part or all of the observation layer comprising cells and reference particles is formed on it;
  • the reference particle actual size DR1 or the reference particle actual area SR1 in the cell suspension sample is known; in the same microscopic image , obtain the reference particle image size DR2 or reference particle image area SR2, and obtain the cell image size DC2 or cell image area SC2;
  • the particle image area SR2 the cell image size DC2 or the cell image area SC2
  • the actual size of the cell DC1 or the actual area of the cell SC1 is obtained by calculation.
  • the technical solution of the present application to solve the above problems can also be a cell analysis method, which is used for cell classification, based on the actual cell size DC1 or cell actual area SC1 obtained above; Cell classification.
  • the technical solution of the present application to solve the above problems can also be a cell analysis method for cell classification, based on a microscopic image;
  • the microscopic image is that cells and reference particles in the cell suspension sample settle on the bearing surface of the carrier At least one microscopic image of part or all of the observation layer comprising cells and reference particles is formed on it; in the same microscopic image, the reference particle image size DR2 or the reference particle image area SR2 is acquired, and the cell image size DC2 is acquired Or cell image area SC2; according to the size relationship between the cell image size DC2 and the reference particle image size DR2, perform cell classification; or according to the size relationship between the cell image area SC2 and the reference particle image area SR2, perform cell classification.
  • the cells with the cell image size DC2 less than or equal to the reference particle image size DR2 are classified as the first type of cells, that is, the cells with DC2 ⁇ DR2 are classified as the first type of cells; or the cell image area SC2 is less than or equal to the reference particle size.
  • the cells with a larger area than the particle image area SR2 are classified as the first type of cells, that is, the cells with SC2 ⁇ SR2 are classified as the first type of cells; the cell image size DC2 is larger than the reference particle image size DR2, and the cell image size DC2 is less than or equal to twice the reference size.
  • Cells with a size DR2 larger than the particle image are classified as the second type of cells, that is, cells with 1DR2 ⁇ DC2 ⁇ 2DR2 are classified as the second type of cells; or the cell image area SC2 is larger than the reference particle image area SR2, and the cell image area SC2 is less than or equal to Cells with twice the reference particle image area SR2 are classified as the second type of cells, that is, cells with 1SR2 ⁇ SC2 ⁇ 2SR2 are classified as the second type of cells; cells with the cell image size DC2 greater than twice the reference particle image size DR2 are classified as The third type of cells, that is, the cells with 2DR2 ⁇ DC2, are classified as the third type of cells; or the cells with the cell image area SC2 greater than twice the reference particle image area SR2 are classified as the third type of cells, that is, the cells with 2SR2 ⁇ SC2 are classified as the third type of cells.
  • the technical solution of the present application to solve the above problems may also be a cell analysis method for obtaining the number of cells in a microscopic image, based on the microscopic image;
  • the microscopic image is cells and reference particles in a cell suspension sample Sedimentation on the bearing surface of the carrier forms at least one microscopic image of part or all of the observation layer including cells and reference particles;
  • the cell image size DC2 or the cell image area SC2 is obtained;
  • obtain the area occupied by all cells ASC2 obtain the area occupied by all cells ASC2; according to the area occupied by all cells ASC2 and cell image size DC2, calculate the number of cells GC in the obtained microscopic image; or according to the area occupied by all cells ASC2 and cell image area SC2, calculate Obtain the number of cells in the microscopic image GC.
  • the technical solution of the present application to solve the above problems may also be a cell analysis method for obtaining the number of reference particles in a microscopic image, based on the microscopic image; the microscopic image is the cells and parameters in the cell suspension sample. At least one microscopic image of part or all of the observation layer comprising cells and reference particles is formed by particle settling on the bearing surface of the carrier; in said microscopic image, the reference particle image size DR2 or the reference particle is obtained Image area SR2; in the microscopic image, obtain the occupied area ASR2 of all reference particles; according to the occupied area ASR2 of all reference particles and the reference particle image size DR2, calculate the number of reference particles GR in the obtained microscopic image; Or calculate the reference particle number GR in the acquired microscopic image based on the area occupied by all reference particles ASR2 and the reference particle image area SR2.
  • the method for acquiring the reference particle number GR in the microscopic image is: in the microscopic image, acquiring the reference particle image size DR2 or the reference particle image area SR2; in the microscopic image , obtain the occupied area ASR2 of all reference particles; according to the occupied area ASR2 of all reference particles and the image size DR2 of the reference particle, calculate the number of reference particles GR in the obtained microscopic image; or according to the occupied area ASR2 of all reference particles and the reference particle size DR2 Calculate the reference particle number GR in the acquired microscopic image by comparing the particle image area SR2.
  • the method for obtaining the reference particle number GR in the microscopic image is: after directly identifying the reference particle according to the shape or size of the reference particle, count all the reference particles to obtain.
  • the technical solution of the present application to solve the above problem may also be a cell analysis method, which is used to obtain the cell concentration in the cell suspension sample, and obtain the volume VM of the cell suspension sample corresponding to the microscopic image imaging based on the obtained microscopic image; Calculate the cell concentration CC in the obtained cell suspension sample based on the cell number GC in the microscopic image and the cell suspension sample volume VM.
  • the method for acquiring the cell number GC in the microscopic image is: in the microscopic image, acquiring the cell image size DC2 or the cell image area SC2; in the microscopic image, acquiring all cells occupied Area ASC2; Calculate the number of cells GC in the acquired microscopic image based on the area occupied by all cells ASC2 and the cell image size DC2; or calculate the number of cells in the acquired microscopic image GC based on the area occupied by all cells ASC2 and the cell image area SC2.
  • the method of obtaining the cell number GC in the microscopic image is: after directly identifying the cells according to the cell shape or cell size, all cells are counted and obtained.
  • the technical solution of the present application to solve the above problems can also be a cell analysis method for obtaining the cell concentration in the original body fluid sample, based on a microscopic image; the microscopic image is the cells and parameters in the cell suspension sample.
  • the concentration CRF of the particle solution is known; when preparing cell suspension samples, the volume VR of the original reference particle solution added is known; when preparing cell suspension samples, the cell concentration CCF of the original body fluid sample is unknown; when preparing cell suspension samples, the The volume V1 of the original body fluid sample added is known
  • the technical solution of the present application to solve the above problems can also be a cell analysis method for obtaining the cell concentration in the original body fluid sample, based on a microscopic image; the microscopic image is the cells and parameters in the cell suspension sample. At least one microscopic image of part or all of the observation layer including cells and reference particles is formed by the sedimentation of the particles on the bearing surface of the carrier; in the microscopic image, all cell numbers GC are obtained; in the microscopic image, Obtain the number of reference particles GR; the concentration CRF of the original reference particle solution is known; when preparing the cell suspension sample, the volume VR of the original reference particle solution added is known; when preparing the cell suspension sample, the concentration of the original body fluid sample The CCF is unknown; when preparing the cell suspension sample, the volume V1 of the original body fluid sample added is known; the CCF is calculated based on the known CRF, VR, V1, GR, and GC.
  • the method for acquiring the cell number GC in the microscopic image is: in the microscopic image, acquiring the cell image size DC2 or the cell image area SC2; in the microscopic image, acquiring all cells occupied Area ASC2; Calculate the number of cells GC in the acquired microscopic image based on the area occupied by all cells ASC2 and the cell image size DC2; or calculate the number of cells in the acquired microscopic image GC based on the area occupied by all cells ASC2 and the cell image area SC2.
  • the method of obtaining the number of cells in the microscopic image GC is: after directly identifying the cells according to the cell shape or cell size, it is obtained by counting all the cells.
  • the method for acquiring the reference particle number GR in the microscopic image is: in the microscopic image, acquiring the reference particle image size DR2 or the reference particle image area SR2; in the microscopic image, acquiring all the reference particles Particle occupied area ASR2; according to all reference particle occupied area ASR2 and reference particle image size DR2, calculate the reference particle number GR in the obtained microscopic image; or according to all reference particle occupied area ASR2 and reference particle image area SR2 , calculate the reference particle number GR in the acquired microscopic image.
  • the method for obtaining the reference particle number GR in the microscopic image is: after directly identifying the reference particle according to the shape or size of the reference particle, count all the reference particles to obtain.
  • the technical solution of the present application to solve the above problems may also be a cell analysis system, including a microscopic image acquisition unit for analysis and a microscopic image analysis unit; the microscopic image acquisition unit for analysis acquires a microscopic image for cell analysis; The microscopic image analysis unit utilizes the above-mentioned cell analysis method to complete cell analysis based on the microscopic image acquired by the microscopic image acquisition unit for analysis.
  • the technical solution of the present application to solve the above problems can also be: a quantitative system, comprising a quantitative analysis microscopic image acquisition unit and a quantitative analysis unit; a quantitative analysis microscopic image acquisition unit to acquire a microscopic image for quantitative analysis; quantitative analysis The unit uses the above-mentioned quantitative method to calculate the volume of the cell suspension sample corresponding to the imaging of the acquired microscopic image based on the quantitative analysis of the microscopic image acquired by the microscopic image acquisition unit.
  • the beneficial effects of the present application are: 1.
  • Cell analysis is performed based on a microscopic image comprising reference particles and cells, since the reference particles are involved in imaging, the reference particles can be used as a scale for counting the number of cells, simplifying
  • the cell counting logic improves the counting accuracy; the cell concentration or number in the original sample can be calculated directly by counting the number of reference particles and cells in the micrograph; the space where the bearing surface is located, that is, the cell nucleus reference particle tile is eliminated.
  • Figure 1 is a schematic diagram of the framework of the cell analysis system.
  • Figure 2 is a schematic diagram of the framework of the cell quantification system.
  • Fig. 3 is a schematic diagram of the production process of blood smear in the prior art.
  • Figure 4 is one of the photographs taken of the observation layer including cells and reference particles.
  • Figure 5 is a second photograph of the observation layer including cells and reference particles.
  • a cell analysis method for obtaining the actual size of cells in a cell suspension sample it is based on a microscopic image that cells and reference particles in the cell suspension sample settle on a carrier surface to form cells comprising cells. and at least one microscopic image of part or all of the observation layer of the reference particle; the reference particle actual size DR1 or the reference particle actual area SR1 in the cell suspension sample is known; in the same microscopic image, the reference particle is obtained.
  • cell image size DC2 or cell image area SC2 Compared with particle image size DR2 or reference particle image area SR2, obtain cell image size DC2 or cell image area SC2; according to reference particle actual size DR1 or reference particle actual area SR1, reference particle image size DR2 or reference particle image The area SR2, the cell image size DC2 or the cell image area SC2 are calculated to obtain the actual cell size DC1 or the actual cell area SC1.
  • the cell suspension sample includes cells and reference particles; the cells and reference particles in the cell suspension sample settle on the bearing surface of the carrier to form an observation layer including cells and reference particles; obtain at least one part or all of the observation layer. Microscopic images for cell analysis.
  • the reference particles and cells are in a microscopic image at the same time, so that each image has a reference particle with known parameters, so each microscopic image can be used for other images with the reference particles of known parameters. information is parsed. If the reference particle size is known, cell analysis is performed based on the relative relationship between the reference particle size and the size of the cells in the image.
  • Cell suspension samples include animal or human body fluid samples; the body fluid samples include blood, urine, semen, saliva, sputum, gynecological secretions, milk, feces, ascites fluid, cerebrospinal fluid, bone marrow, tears, nasal mucus any one or more of them.
  • cell suspension samples including diluent and/or staining solution; in cell suspension samples, body fluid and diluent are evenly mixed; or in cell suspension samples, body fluid and staining solution are evenly mixed; or in cell suspension samples, body fluid, diluted solution The liquid and the dyeing liquid are mixed evenly.
  • the staining solution includes fluorescent staining solution. Microorganisms are included in the cell suspension sample.
  • Reference particles include gold particles, silver particles, carbon particles, ferric oxide particles, silica particles, polystyrene particles, polypropylene particles, polycarbonate particles, ceramic particles, chitosan particles, cellulose particles. any one or more.
  • the reference particles include magnetic bead particles; the magnetic bead particles include Fe3O4 particles.
  • the material of the reference particles can be selected according to different scenarios. Different body fluid samples contain different cell characteristics, such as the size of the cells and the electrical properties of the cells; the shapes of the reference particles include spheres, cones, Any one or more of the cuboids.
  • the shape of the reference particles can be selected according to the characteristics of the cells to be analyzed, and can be a shape that is significantly different from the characteristics of the cells, or a shape that is similar to the characteristics of the cells.
  • the shape difference feature can be used for cell analysis and identification.
  • Reference particles can also be used for cell analysis and identification when they are similar in shape to cells.
  • the reference particle is spherical, and the diameter of the sphere is used as the actual size DR1 of the reference particle; the image size DR2 of the reference particle is the size of the diameter of the sphere in the image; the image area SR2 of the reference particle is the plane projection of the sphere area.
  • the projection obtained in the microscopic image may be a non-orthogonal projection of an ellipse or a circular orthographic projection; the approximate area can be taken in the actual calculation.
  • the shape of the reference particle is a cone, the height of the cone or the width of the base of the cone is used as the actual size DR1 of the reference particle; the image size DR2 of the reference particle is the height of the cone or the base of the cone The size of the width in the image.
  • the image area SR2 of the reference particle can be the non-orthographic projection of the ellipse of the cone, or the orthographic projection of the circle; the approximate area can be taken in the actual calculation.
  • the shape of the reference particle is a cuboid, and any side length of the cuboid is used as the actual size DR1 of the reference particle; the image size DR2 of the reference particle is the size of the cuboid in the image.
  • the image area SR2 of the reference particle may be the projected area of the cuboid.
  • a cuboid also includes a cube; when the cuboid is a cube, there is only one side dimension.
  • the concentration CR of the reference particle in the cell suspension sample is known.
  • the reference particle actual size DR1 or the reference particle actual area SR1 is known.
  • the actual size DR1 of the reference particles ranges from 1 ⁇ m to 100 ⁇ m.
  • the reference particle actual area SR1 can be calculated from the size range and shape.
  • Reference particles of different shapes can exist in the same cell suspension sample, and the size of reference particles of different shapes can be the same or different; reference particles of different shapes or sizes are in the same cell suspension sample. Use as a reference identification for different cell classifications or counts.
  • Cell image size DC2 or cell image area SC2 refers to the size of cells displayed in the image.
  • the maximum width in the plane image can be taken as the cell image size DC2 or cell image area SC2.
  • the diameter of the circular projection in the image is taken as the cell image size DC2 or the cell image area SC2, and the cell area is ⁇ DC2 ⁇ DC2/4.
  • the side length of the square projection in the image is taken as the cell image size DC2 or the cell image area SC2, and the cell area is DC2 ⁇ DC2.
  • the area of the cell image can be calculated by a square area calculation formula or a circular area calculation formula.
  • Figures 4 and 5 are two images obtained from the observation layer including cells and reference particles.
  • red blood cells are in the square box; reference particles are in the round box.
  • reference particles are in the round box.
  • white blood cells are shown in the oval box in Figure 5.
  • the sample forming Figure 4 is a cat venous whole blood sample, and the reference particles are magnetic micro-spherical particles with a diameter of 3um.
  • the sample forming Figure 5 was a cat venous whole blood sample, and the reference particles were spherical polystyrene particles with a diameter of 5 microns.
  • a certain number of micrographs, ie, microscopic images, are obtained by taking pictures, and Fig. 5 is one of them.
  • the actual cell size DC1 or the cell actual area SC1 obtained above; the cell classification is performed according to the size interval of the cell actual size DC1 or the actual cell area SC1.
  • Various textbooks or other reference books have cell diameter range data for cell classification. After the actual cell size obtained above is obtained, the cells can be classified according to the data corresponding to the cell size.
  • the microscopic image on which it is based is the same as in the above-mentioned embodiment; in the same microscopic image, the reference particle image size DR2 or the reference particle image area are obtained SR2, obtain the cell image size DC2 or the cell image area SC2; according to the size relationship between the cell image size DC2 and the reference particle image size DR2, or according to the size relationship between the cell image area SC2 and the reference particle image area SR2, perform cell classification.
  • cells with a cell image size DC2 less than or equal to a reference particle image size DR2 are classified as cells of the first type, that is, cells with DC2 ⁇ DR2 are classified as cells of the first type ; Classify the cells with the cell image size DC2 greater than the reference particle image size DR2, and the cell image size DC2 less than or equal to twice the reference particle image size DR2 as the second type of cells, that is, cells with 1DR2 ⁇ DC2 ⁇ 2DR2 are classified as the second type of cells Cell-like cells; cells whose cell image size DC2 is greater than twice the reference particle image size DR2 are classified as the third type of cells, that is, cells with 2DR2 ⁇ DC2 are classified as the third type of cells.
  • the cells with the cell image area SC2 less than or equal to the reference particle image area SR2 are classified as the first type of cells, that is, the cells with SC2 ⁇ SR2 are classified as the first type of cells. ;
  • the cell image area SC2 is greater than the reference particle image area SR2, and the cell image area SC2 is less than or equal to twice the reference particle image area SR2
  • the cells are classified as the second type of cells, that is, the cells with 1SR2 ⁇ SC2 ⁇ 2SR2 are classified as the second type of cells.
  • Cell-like cells; cells whose cell image area SC2 is greater than twice the reference particle image area SR2 are classified as the third type of cells, that is, cells with 2SR2 ⁇ SC2 are classified as the third type of cells.
  • reference particles with an actual diameter size of 5um are selected; used for cell sorting. From the microscopic image, obtain the diameter data of each cell in the microscopic image, and classify the cells according to the size relationship between the reference particle image size DR2 and the cell image size DC2, or according to or the reference particle image area SR2 and the cell image The size relationship between the area SC2 was used for cell classification. Cells with DC2 ⁇ DR2 were classified as the first type of cells; cells with 1DR2 ⁇ DC2 ⁇ 2DR2 were classified as the second type of cells; cells with 2DR2 ⁇ DC2 were classified as the third type of cells.
  • DC2 ⁇ DR2 were classified as the first type of cells
  • cells with 1DR2 ⁇ DC2 ⁇ 2DR2 were classified as the second type of cells
  • cells with 2DR2 ⁇ DC2 were classified as the third type of cells.
  • the human body fluid sample included in the cell suspension sample is a blood sample
  • the first type of cells may be platelets
  • the second type of cells may be red blood cells
  • the third type of cells may be white blood cells.
  • different organisms have different cell sizes in their samples, and the size of the reference particles can be flexibly selected according to the actual application scenario.
  • the actual cell size table As shown in Figure 6, the actual cell size table.
  • the data in the table is obtained by the AI image recognition system based on the scale in the system and the number of pixels occupied by each cell diameter dimension in the microscopic image.
  • the sample used was cat blood.
  • Red blood cell (RBC) size ranges from 6.0um to 7.0um
  • white blood cell (WBC) size ranges from 9.0um to 20.0um
  • platelets (PLT) size ranges from 2.2um to 20.0um 2.7um.
  • the data obtained from Fig. 6 are shown in the table. According to the data in the table, the classification and counting results of different cells can be obtained: the total number of cells in the picture is 120; red blood cells (RBC) 116, white blood cells (WBC) 1, platelets ( PLT) 13.
  • RBC red blood cells
  • WBC white blood cells
  • PLT platelets
  • Cell counts can also be performed based on the size relationships of the various cell types and reference particles described above.
  • reference particles it is more convenient to use the reference particles to count according to the size relationship, without paying attention to the specific size of each cell, only pay attention to the relative size relationship for cell classification.
  • reference particles of different sizes can be selected.
  • the microscopic image on which it is based is the same as in the above-described embodiment; in the microscopic image, the cell image size DC2 or cell image is acquired Area SC2; in the microscopic image, obtain the area occupied by all cells ASC2; according to the area occupied by all cells ASC2 and cell image size DC2, calculate the number of cells GC in the obtained microscopic image; or according to the area occupied by all cells ASC2 and cell image area SC2, count the number of cells GC in the acquired microscopic images.
  • the microscopic image on which it is based is the same as in the above-mentioned embodiment; in the microscopic image, the size of the reference particle image is obtained DR2 or reference particle image area SR2; in the microscopic image, obtain the occupied area ASR2 of all reference particles; according to the occupied area ASR2 of all reference particles and the reference particle image size DR2, calculate and obtain the reference particle in the microscopic image.
  • the specific particle number GR; or the reference particle number GR in the acquired microscopic image is calculated according to the occupied area ASR2 of all reference particles and the reference particle image area SR2.
  • the volume of the cell suspension sample corresponding to the obtained microscopic image imaging is calculated, and the microscopic image on which it is based is the same as that in the above-mentioned embodiment;
  • the concentration of the reference particle in the cell suspension sample, RC is units/ml, ie units per milliliter.
  • the fresh EDTA.K 2 intravenous anticoagulated whole blood of dogs was used as the sample, the material was Fe 3 O 4 (iron tetroxide), the shape was spherical, the diameter was 3.0um, and the concentration was 2.15 ⁇ 10 9 particles/ml as the reference particle in this example.
  • the original concentration of reference particles refers to the concentration of reference particles in the original reference particle solution, and the unit is units/ml.
  • the volume VM of the cell suspension sample corresponding to the obtained microscopic image imaging is obtained based on the above; the cell number GC in the microscopic image is obtained; Cell number GC and cell suspension sample volume VM in the micro-image, calculation to obtain the cell concentration CC in the cell suspension sample.
  • the fresh EDTA.K 2 intravenous anticoagulated whole blood of dogs was used as the sample, the material was Fe 3 O 4 (iron tetroxide), the shape was spherical, the diameter was 3.0um, and the concentration was 2.15 ⁇ 10 9 particles/ml as the reference particle in this example. Take 10.0ul fully mixed blood sample and 10.0ul original reference particle solution including reference particles and add them to 980.0ul staining solution. Acquire 350 micrographs at a time in the micro-imaging system.
  • the fresh EDTA.K 2 intravenous anticoagulated whole blood of dogs was used as the sample, the material was Fe 3 O 4 (iron tetroxide), the shape was spherical, the diameter was 3.0um, and the concentration was 2.15 ⁇ 10 9 particles/ml as the reference particle in this example. Take 10.0ul fully mixed blood sample and 10.0ul original reference particle solution including reference particles and add them to 980.0ul staining solution. Acquire 350 micrographs at a time in the micro-imaging system.
  • the fresh EDTA.K 2 intravenous anticoagulated whole blood of dogs was used as the sample, the material was Fe 3 O 4 (iron tetroxide), the shape was spherical, the diameter was 3.0um, and the concentration was 2.15 ⁇ 10 9 particles/ml as the reference particle in this example. Take 10.0ul fully mixed blood sample and 10.0ul original reference particle solution including reference particles and add them to 980.0ul staining solution. Acquire 350 micrographs at a time in the micro-imaging system.
  • ASC2/ASR2 CCF ⁇ V1 ⁇ DC2 ⁇ DC2/(CRF ⁇ VR ⁇ DR2 ⁇ DR2)
  • ASC2/ASR2 CCF ⁇ V1 ⁇ SC2/(CRF ⁇ VR ⁇ SR2)
  • the fresh EDTA.K 2 intravenous anticoagulated whole blood of dogs was used as the sample, the material was Fe 3 O 4 (iron tetroxide), the shape was spherical, the diameter was 3.0um, and the concentration was 2.15 ⁇ 10 9 particles/ml as the reference particle in this example. Take 10.0ul fully mixed blood sample and 10.0ul original reference particle solution including reference particles and add it to 980.0ul staining solution. Acquire 350 micrographs at a time in the micro-imaging system.
  • the method of obtaining the cell number GC in the microscopic image is: in the microscopic image, obtaining the cell image size DC2 or the cell image area SC2; in the microscopic image, obtaining The
  • the method for obtaining the cell number GC in the microscopic image is to directly identify cells according to cell morphology or cell size Afterwards, all cell counts were obtained.
  • the method for obtaining the reference particle number GR in the microscopic image is: in the microscopic image, obtaining the reference particle image size DR2 Or the reference particle image area SR2; in the microscopic image, obtain the occupied area ASR2 of all reference particles; according to the occupied area ASR2 of all reference particles and the reference particle image size DR2, calculate the number of reference particles in the obtained microscopic image GR; or calculate the number GR of reference particles in the acquired microscopic image based on the area occupied by all reference particles ASR2 and the area of the reference particle image SR2.
  • the method for obtaining the reference particle number GR in the microscopic image is: directly identifying the reference particle shape or the reference particle size according to the reference particle shape or the reference particle size. After reference particles are obtained, all reference particles are counted.
  • the statistical value of the size is used as the cell image size of this image, and the statistical value of the cell image size of a plurality of microscopic images is taken as the cell image size DC2 or the cell image area SC2.
  • the cell image size DC2 or the cell image area SC2 can have multiple sources, one of which is a single size-representative cell image size in a single microscopic image; the other is multiple microscopic images.
  • the statistical value of the size of a single representative cell image; three of them are the statistical value of the size of multiple cell images in a single microscopic image.
  • the statistical value includes the average, and the statistical value also includes other statistical methods, such as Statistical processing is carried out according to distribution probability or confidence interval; the fourth one is based on the third method, taking the statistical value of the size of multiple cell images in each single microscopic image in multiple microscopic images, and then taking the statistical value.
  • the image size DR2 or image area SR2 of the reference particle is also obtained using the method described above.
  • an embodiment of the cell analysis system includes a microscopic image acquisition unit for analysis and a microscopic image analysis unit; a microscopic image acquisition unit for analysis acquires a microscopic image for cell analysis; The image analysis unit performs cell analysis based on the microscopic image acquired by the microscopic image acquisition unit for analysis using the above-described cell analysis method.
  • an embodiment of the quantitative system includes a quantitative analysis microscopic image acquisition unit and a quantitative analysis unit; the quantitative analysis microscopic image acquisition unit is used to acquire a microscopic image for quantitative analysis; the quantitative analysis unit utilizes
  • the volume of the cell suspension sample corresponding to the imaging of the acquired microscopic image is calculated based on the quantitative analysis of the microscopic image acquired by the microscopic image acquisition unit.
  • a cell suspension sample imaging subsystem may be included.
  • the cell suspension sample imaging subsystem provides microscopic images to the analytical microscopic image acquisition unit or the quantitative analysis microscopic image acquisition unit.
  • the microscopic image acquisition unit for analysis and the cell suspension sample imaging subsystem can be wired or wirelessly connected to acquire microscopic image information; also, there can be a wired connection between the quantitative analysis microscopic image acquisition unit and the cell suspension sample imaging subsystem Electrical connection or radio connection to obtain microscopic image information.
  • the cell suspension sample includes cells and reference particles; a carrier is used to carry the cell suspension sample; the carrier includes a bearing surface; the cell suspension After the liquid sample enters the carrier, the cells and reference particles in the cell suspension sample settle on the carrier surface to form an observation layer including cells and reference particles; the microscopic image acquisition unit is used to obtain observations including cells and reference particles at least one image of the layer.
  • the microscopic image acquisition unit includes a device with an imaging function, such as a CCD imaging device or other devices that can digitally record or present a microscopic image. These devices can capture and record microscopic images obtained by microscopes to form electronic files.
  • Microscopic image acquisition units include fluorescence microscopes or ordinary light microscopes.
  • the reference particle After the reference particle is involved in the imaging, the reference particle can be used as a quantitative scale for subsequent calculations, which simplifies the calculation logic and the accuracy of the calculation.
  • the cell suspension sample includes reagents, samples and reference particles. After the three are fully mixed, the tiling and distribution of the reference particles in the observation layer is consistent with that in the sample to be tested.
  • the concentration or number of cells in the original sample can be calculated directly by counting the size, area or number relationship between the reference particles and cells in the micrograph, without considering other factors such as the volume and area of the observation area ; That is, the space where the bearing surface is located, that is, the depth of the tiling area of the nucleus reference particles, and the size of the field of view, greatly reduce the impact on imaging and subsequent calculations.
  • the counting accuracy is improved when using the imaging image for cell counting.
  • the traditional counting logic it is more dependent on the processing accuracy of the counting plate, especially the volume of the tiling and distribution area.
  • the process error of the volume of the tiling and distribution area directly affects the number of cells, thereby counting the results; while adding the reference particles of the internal standard, the cell counting logic has nothing to do with the volume of the tiling and distribution area.
  • the reference particle After the reference particle participates in the imaging, the reference particle can be used as an autofocus reference to correct the imaging quality; the reference particle has size uniformity. During the detection process of a sample, the observation and counting of multiple fields of view will be involved.
  • the reference particles with standard size are used as the focus reference point to achieve the uniformity of image focus, thereby enhancing the image quality and improving the accuracy of the results.

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Abstract

一种细胞分析方法和系统，所基于显微图像是细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层的部分或全部的至少一幅显微图像；细胞悬浮液样品中的参比粒子实际尺寸DR1或参比粒子实际面积SR1已知；基于已知的参比粒子特征信息进行细胞分析，细胞分析包括细胞尺寸、细胞分类、细胞计数、参比粒子计数、显微图像成像对应的细胞悬浮液样品体积的定量、细胞悬浮液样品中的细胞浓度、原始的身体液体样本中的细胞浓度。利用参比粒子参与成像的显微图像，参与成像的细胞悬浮液样品能定量计算，简化了细胞分类方法和细胞计数方法，提高了计数准确性。

Description

细胞分析方法和系统及定量方法和系统 技术领域
本申请属于细胞分析方法和系统领域；尤其涉及基于细胞悬浮液样品的成像后获得的显微图像进行细胞分析的方法和系统。
背景技术
如图3所示，是现有技术中一个血涂片的制作过程示意图，由图可见其包括血涂片制作的步骤和血涂片染色的步骤。
血涂片制作的步骤中包括四个小步骤：分别是，步骤1.1：将血样滴加至载玻片上；步骤1.2：取另一载玻片，按30°～45°角倾斜，匀速向另一边推动；步骤1.3：血膜涂布均匀，呈“火焰”状为合格的涂片；步骤1.4：等待血膜干燥，并准备染色。
涂片染色的步骤中包括五个小步骤：分别是，步骤2.1：铅笔作标记，将血涂片平放在染色架上,蜡笔划线可防液体外溢；步骤2.2：血涂片自然干燥后，滴染液1～2滴覆盖血片,染约1分钟；步骤2.3：滴加稍多体积如2～4滴)的缓冲液，用洗耳球将其与染液吹匀,染约5分钟；步骤2.4：慢慢摇动玻片，然后用细的自来水流从玻片的一侧冲去染液(注意，需要不要先倒去染液再冲水)，持续约1分钟；步骤2.5：终止冲洗，将血片自然干燥后或用滤纸吸干，即可用于镜检。
用于镜检的涂片上的细胞数量是通过人工在显微镜下进行观察和计数，观察效率极低。不光是在明场镜检的场景中，在一些荧光成像镜检的场景中，也存在明场检测类似的问题，观察和计数都效率低下。且在观察过程中，每次成像图片的放大倍数可能不同，对只能根据经验进行细胞分类和计数；无法对图像中的细胞尺寸进行精确的计算。
技术问题
现有技术中，有利用染色后的细胞悬浮液样品进行细胞计数的场景中，其计数逻辑是通过引入可承载独立细胞的计数承载面网进行细胞计数；承载面网上与单个隔间尺寸相应的细胞才能被很好的承载展示，并用于细胞识别和计数。由于细胞的种类繁多，不同的细胞需要设计适应不同细胞尺寸的承载面网。且其计数的准确性更多依赖于计数板即形成观察层的承载面网的结构和加工精度，尤其是细胞平铺区或分布区域的体积，当加工精度不够时，误差很大，相应地细胞的识别和分类计数误差也大大增加。
迫切需要采用数字化手段进行图像的处理，对图像中的各种信息进行精确处理和分析；在现在智能算法快速发展的背景下，在图像中识别出单一的细胞或进行细胞计数是容易 的，但要通过单幅照片获取原始样本中的细胞浓度却并比较困难；最关键的问题是单幅照片所对应的细胞悬浮液样品的量无法准确获取。而在本发明中，由于参比粒子的引入，可以通过参比粒子在照片或图像中的分布情况获取单幅照片对应的细胞悬浮液样品体积，从而以此为基础进行更准确的细胞计数和细胞浓度计算。
本申请中um是微米；ul是微升；ml是毫升。
技术解决方案
本申请要解决的技术问题在于避免现有技术上述不足之处，提出了一种简单高效的细胞分析方法，通过参比粒子参与形成观察层，能利用参比粒子进行细胞分析，提高细胞分析尤其是细胞计数和细胞浓度计算的综合效率，且提高了计算的准确性，能降低系统误差在细胞分析中的影响。
本申请解决上述问题的技术方案一种用于获取细胞悬浮液样品中细胞实际尺寸，基于显微图像；所述显微图像是细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层的部分或全部的至少一幅显微图像；细胞悬浮液样品中的参比粒子实际尺寸DR1或参比粒子实际面积SR1已知；在同一显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2，获取细胞图像尺寸DC2或细胞图像面积SC2；根据参比粒子实际尺寸DR1或参比粒子实际面积SR1、参比粒子图像尺寸DR2或参比粒子图像面积SR2、细胞图像尺寸DC2或细胞图像面积SC2，计算获得细胞实际尺寸DC1或细胞实际面积SC1。
本申请解决上述问题的技术方案还可以是一种细胞分析方法，用于细胞分类，基于上述获得的细胞实际尺寸DC1或细胞实际面积SC1；按照细胞实际尺寸DC1或细胞实际面积SC1的大小区间进行细胞分类。
本申请解决上述问题的技术方案还可以是一种细胞分析方法，用于细胞分类，基于显微图像；所述显微图像是细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层的部分或全部的至少一幅显微图像；在同一显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2，获取细胞图像尺寸DC2或细胞图像面积SC2；依据细胞图像尺寸DC2和参比粒子图像尺寸DR2的大小关系，进行细胞分类；或依据细胞图像面积SC2和参比粒子图像面积SR2的大小关系，进行细胞分类。
所述细胞分析方法，将细胞图像尺寸DC2小于等于参比粒子图像尺寸DR2的细胞分类为第一类细胞，即DC2≤DR2的细胞分类为第一类细胞；或将细胞图像面积SC2小于等于参比粒子图像面积SR2的细胞分类为第一类细胞，即SC2≤SR2的细胞分类为第一类细胞； 将细胞图像尺寸DC2大于参比粒子图像尺寸DR2，且细胞图像尺寸DC2小于等于两倍参比粒子图像尺寸DR2的细胞分类为第二类细胞，即1DR2＜DC2≤2DR2的细胞分类为第二类细胞；或将细胞图像面积SC2大于参比粒子图像面积SR2，且细胞图像面积SC2小于等于两倍参比粒子图像面积SR2的细胞分类为第二类细胞，即1SR2＜SC2≤2SR2的细胞分类为第二类细胞；将细胞图像尺寸DC2大于两倍参比粒子图像尺寸DR2的细胞分类为第三类细胞，即2DR2＜DC2的细胞分类为第三类细胞；或将细胞图像面积SC2大于两倍参比粒子图像面积SR2的细胞分类为第三类细胞，即2SR2＜SC2的细胞分类为第三类细胞。
本申请解决上述问题的技术方案还可以是一种细胞分析方法，用于获取显微图像中的细胞数量，基于显微图像；所述显微图像是细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层的部分或全部的至少一幅显微图像；在所述显微图像中，获取细胞图像尺寸DC2或细胞图像面积SC2；在所述显微图像中，获取所有细胞占据面积ASC2；根据所有细胞占据面积ASC2和细胞图像尺寸DC2，计算获取显微图像中的细胞数量GC；或根据所有细胞占据面积ASC2和细胞图像面积SC2，计算获取显微图像中的细胞数量GC。
本申请解决上述问题的技术方案还可以是一种细胞分析方法，用于获取显微图像中的参比粒子数量，基于显微图像；所述显微图像是细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层的部分或全部的至少一幅显微图像；在所述显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2；在所述显微图像中，获取所有参比粒子占据面积ASR2；根据所有参比粒子占据面积ASR2和参比粒子图像尺寸DR2，计算获取显微图像中的参比粒子数量GR；或根据所有参比粒子占据面积ASR2和参比粒子图像面积SR2，计算获取显微图像中的参比粒子数量GR。
本申请解决上述问题的技术方案还可以是一种定量方法，用于细胞悬浮液样品的定量，即计算获取显微图像成像对应的细胞悬浮液样品体积，基于显微图像；所述显微图像是细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层的部分或全部的至少一幅显微图像；获取显微图像中的参比粒子数量GR；参比粒子在细胞悬浮液样品中的浓度RC已知；获取显微图像成像对应的细胞悬浮液样品体积VM＝GR/RC。
所述定量方法，获取显微图像中的参比粒子数量GR的方法是：在所述显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2；在所述显微图像中，获取所有参比粒子占据面积ASR2；根据所有参比粒子占据面积ASR2和参比粒子图像尺寸DR2，计算获取显微图像中的参比粒子数量GR；或根据所有参比粒子占据面积ASR2和参比粒子图像面积 SR2，计算获取显微图像中的参比粒子数量GR。
获取显微图像中的参比粒子数量GR的方法是：根据参比粒子形态或参比粒子大小直接识别出参比粒子后，对所有参比粒子计数获得。
本申请解决上述问题的技术方案还可以是一种细胞分析方法，用于获取细胞悬浮液样品中的细胞浓度，基于上述获得显微图像成像对应的细胞悬浮液样品体积VM；获取显微图像中的细胞数量GC；根据显微图像中的细胞数量GC和细胞悬浮液样品体积VM，计算获取细胞悬浮液样品中的细胞浓度CC。计算公式为CC＝GC/VM。
所述细胞分析方法，获取显微图像中的细胞数量GC的方法是：在所述显微图像中，获取细胞图像尺寸DC2或细胞图像面积SC2；在所述显微图像中，获取所有细胞占据面积ASC2；根据所有细胞占据面积ASC2和细胞图像尺寸DC2，计算获取显微图像中的细胞数量GC；或根据所有细胞占据面积ASC2和细胞图像面积SC2，计算获取显微图像中的细胞数量GC。
所述细胞分析方法，获取显微图像中的细胞数量GC的方法是：根据细胞形态或细胞大小直接识别出细胞后，对所有细胞计数获得。
本申请解决上述问题的技术方案还可以是一种细胞分析方法，用于获取原始的身体液体样本中的细胞浓度，基于权利要求10获得的细胞悬浮液样品中的细胞浓度CC；制备细胞悬浮液样品时，原始的身体液体样本的稀释比率X已知；原始的身体液体样本中的细胞浓度CCF＝CC/X。
本申请解决上述问题的技术方案还可以是一种细胞分析方法，用于获取原始的身体液体样本中的细胞浓度，基于显微图像；所述显微图像是细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层的部分或全部的至少一幅显微图像；在显微图像中，获取所有细胞占据面积ASC2；在显微图像中，获取细胞图像尺寸DC2或细胞图像面积SC2；在显微图像中，获取所有参比粒子占据面积ASR2；在显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2；原始参比粒子溶液的浓度CRF已知；制备细胞悬浮液样品时，加入原始参比粒子溶液体积VR已知；制备细胞悬浮液样品时，原始的身体液体样本细胞浓度CCF未知；制备细胞悬浮液样品时，加入原始的身体液体样本的体积V1已知；依据已知的ASC2、ASR2、V1、DC2、CRF、VR、DR2，获取原始的身体液体样本的细胞浓度CCF；或依据ASC2、ASR2、V1、SC2、CRF、VR、SR2，获取原始的身体液体样本的细胞浓度CCF。
本申请解决上述问题的技术方案还可以是一种细胞分析方法，用于获取原始的身体液 体样本中的细胞浓度，基于显微图像；所述显微图像是细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层的部分或全部的至少一幅显微图像；在显微图像中，获取所有细胞个数GC；在显微图像中，获取参比粒子个数GR；原始参比粒子溶液的浓度CRF已知；制备细胞悬浮液样品时，加入原始参比粒子溶液体积VR已知；制备细胞悬浮液样品时，原始的身体液体样本浓度CCF未知；制备细胞悬浮液样品时，加入原始的身体液体样本体积V1已知；根据已知的CRF、VR、V1、GR、GC计算获得CCF。
所述细胞分析方法，获取显微图像中的细胞数量GC的方法是：在所述显微图像中，获取细胞图像尺寸DC2或细胞图像面积SC2；在所述显微图像中，获取所有细胞占据面积ASC2；根据所有细胞占据面积ASC2和细胞图像尺寸DC2，计算获取显微图像中的细胞数量GC；或根据所有细胞占据面积ASC2和细胞图像面积SC2，计算获取显微图像中的细胞数量GC。
获取显微图像中的细胞数量GC的方法是：根据细胞形态或细胞大小直接识别出细胞后，对所有细胞计数获得。
获取显微图像中的参比粒子数量GR的方法是：在所述显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2；在所述显微图像中，获取所有参比粒子占据面积ASR2；根据所有参比粒子占据面积ASR2和参比粒子图像尺寸DR2，计算获取显微图像中的参比粒子数量GR；或根据所有参比粒子占据面积ASR2和参比粒子图像面积SR2，计算获取显微图像中的参比粒子数量GR。
获取显微图像中的参比粒子数量GR的方法是：根据参比粒子形态或参比粒子大小直接识别出参比粒子后，对所有参比粒子计数获得。
本申请解决上述问题的技术方案还可以是一种细胞分析系统，包括分析用显微图像获取单元和显微图像分析单元；分析用显微图像获取单元，获取用于细胞分析的显微图像；显微图像分析单元利用上述的细胞分析方法，基于分析用显微图像获取单元获取的显微图像完成细胞分析。
本申请解决上述问题的技术方案还可以是.一种定量系统，包括定量分析显微图像获取单元和定量分析单元；定量分析显微图像获取单元，获取用于定量分析的显微图像；定量分析单元利用上述述的定量方法，基于定量分析显微图像获取单元获取的显微图像，计算获取显微图像成像对应的细胞悬浮液样品体积。
有益效果
同现有技术相比较，本申请的有益效果是：1.基于包括参比粒子和细胞的显微图像进 行细胞分析，由于参比粒子参与成像，参比粒子可以用作细胞计数数量标尺，简化细胞计数逻辑，提升计数准确性；可直接通过计数显微图片中参比粒子与细胞的数量，来计算原始样本中的细胞浓度或数量；消除了承载面所处空间即细胞核参比粒子平铺区域的深度、视野的大小对细胞计数结果的影响。
附图说明
图1是细胞分析系统的框架示意图。
图2是细胞定量系统的框架示意图。
图3是现有技术中血涂片制作过程示意图。
图4是包括细胞和参比粒子的观察层获得的照片之一。
图5是包括细胞和参比粒子的观察层获得的照片之二。
本发明的最佳实施方式
以下结合各附图对本申请的实施方式做进一步详述。
用于获取细胞悬浮液样品中细胞实际尺寸的一种细胞分析方法的实施例中，其所基于显微图像是细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层的部分或全部的至少一幅显微图像；细胞悬浮液样品中的参比粒子实际尺寸DR1或参比粒子实际面积SR1已知；在同一显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2，获取细胞图像尺寸DC2或细胞图像面积SC2；根据参比粒子实际尺寸DR1或参比粒子实际面积SR1、参比粒子图像尺寸DR2或参比粒子图像面积SR2、细胞图像尺寸DC2或细胞图像面积SC2，计算获得细胞实际尺寸DC1或细胞实际面积SC1。
计算细胞实际尺寸DC1的公式是：DC1＝DR1×DC2/DR2；计算细胞实际面积SC1的公式是：SC1＝SR1×SC2/SR2。细胞悬浮液样品中包括细胞和参比粒子；细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层；获取观察层部分或全部的至少一幅显微图像，用于细胞分析。
参比粒子和细胞同时在一副显微图像中，使每一副图像都具有一个已知参数的参比粒子，因此每一幅显微图像都能借助已知参数的参比粒子进行其他图像信息进行解析。若参比粒子大小已知，则根据参比粒子大小和图像中细胞大小之间的相对关系，进行细胞分析。
细胞悬浮液样品中包括动物或人的身体液体样本；所述身体液体样本包括血液、尿液、精液、唾液、痰液、妇科分泌物、乳汁、粪便、腹水液、脑脊液、骨髓、泪液、鼻涕中的任意一种或多种。
细胞悬浮液样品中,包括稀释液和或染色液；细胞悬浮液样品中,体液和稀释液混合均 匀；或细胞悬浮液样品中,体液和染色液混合均匀；或细胞悬浮液样品中体液、稀释液和染色液三者混合均匀。
染色液包括荧光染色液。细胞悬浮液样品中包括微生物。
参比粒子包括金粒子、银粒子、碳粒子、四氧化三铁粒子、氧化硅粒子、聚苯乙烯粒子、聚丙烯粒子、聚碳酸酯粒子、陶瓷粒子、壳聚糖粒子、纤维素粒子中的任意一种或多种。参比粒子中包括磁珠粒子；磁珠粒子中包括四氧化三铁Fe 3O 4粒子。
参比粒子的材质可以根据不同的场景进行选择，不同的身体液体样本中所包含的细胞特征不同，如细胞的大小、细胞的电学特性不同；所述参比粒子的形状包括球体、锥体、长方体中的任意一种或多种。
参比粒子的形状可以根据待分析细胞的特征进行选择，可以选择和细胞特征差异大的形状，也可以选择和细胞特征相似的形状。参比粒子的形状和细胞的形状差异大时，可以利用形状差异特征进行细胞分析和鉴别。参比粒子形状和细胞形状相似时，也可以用来进行细胞分析和鉴别。
参比粒子为球形，球形的直径用作参比粒子的实际尺寸DR1；参比粒子的图像尺寸DR2是所述球形的直径在图像中的尺寸；参比粒子的图像面积SR2是球形的平面投影的面积。在显微图像中获得的投影可能是椭圆形的非正投影，也可能是圆形的正投影；实际计算中可以取近似面积。
参比粒子的形状为锥体，锥体的高度或锥体的底面宽度用作参比粒子的实际尺寸DR1；参比粒子的图像尺寸DR2是所述锥体的高度或所述锥体的底面宽度在图像中的尺寸。参比粒子的图像面积SR2可以是锥体的椭圆形的非正投影，也可能是圆形的正投影；实际计算中可以取近似面积。
参比粒子的形状为长方体，长方体任意边长用作的参比粒子的实际尺寸DR1；参比粒子的图像尺寸DR2是所述长方体在图像中的尺寸。参比粒子的图像面积SR2可以是长方体的投影面积。长方体也包括正方体；当长方体为立方体时，只有一个边长尺寸。
参比粒子在细胞悬浮液样品中的浓度CR已知。参比粒子实际尺寸DR1或参比粒子实际面积SR1已知。
参比粒子实际尺寸DR1范围是1μm-100μm。参比粒子实际面积SR1可以根据尺寸范围和形状进行计算。
不同形状的参比粒子可以存在于同一次的细胞悬浮液样品中，不同的形状的参比粒子尺寸可以相同也可以不同；不同形状或不同尺寸的参比粒子在同一次的细胞悬浮液样品中用 作不同的细胞分类或计数的参比识别。
细胞图像尺寸DC2或细胞图像面积SC2，是指细胞在图像中显示的大小，不同形态的细胞，可以取平面图像中的最大宽度用作细胞图像尺寸DC2或细胞图像面积SC2。当然对球形细胞，取图像中圆形投影的直径用作细胞图像尺寸DC2或细胞图像面积SC2，细胞面积是π×DC2×DC2/4。对其他形态的细胞，取图像中方形投影的边长用作细胞图像尺寸DC2或细胞图像面积SC2，细胞面积是DC2×DC2。细胞图像的面积可以采用方形面积计算公式也可以采用圆形面积计算公式。
图4和图5是包括细胞和参比粒子的观察层获得的两幅图像，图4和图5中正方形选框中的为红细胞；圆形选框中的为参比粒子。图4中的圆形选框中有两个参比粒子。图5中椭圆形框中为白细胞。
形成图4的样本为猫静脉全血样本，参比粒子为直径为3um的磁性微米球形颗粒。将10ul上述血液样本，与10ul包括参比粒子的原始参比粒子溶液，加入到980ul总体积的染色试剂中，颠倒混匀1分钟，然后将混合液加入到观察载体上，用光学显微镜成像后进行拍照即获得一定数量的显微照片即显微图像，图4为其中之一。
形成图5的样本为猫静脉全血样本，参比粒子为直径为5微米的聚苯乙烯球形颗粒。将10ul上述血液样本，与10ul包括参比粒子的原始参比粒子溶液，加入到980ul总体积的染色试剂中，颠倒混匀1分钟，然后将混合液加入到观察载体上，用光学显微镜成像后进行拍照即获得一定数量的显微照片即显微图像，图5为其中之一。
用于获取细胞悬浮液样品中细胞实际尺寸的一种细胞分析方法的实施例中，其所基于的显微图像和上述实施例相同，且显微图像的放大倍数A已知；在显微图像中，获取细胞图像尺寸DC2或细胞图像面积SC2；根据显微图像的放大倍数A和细胞图像尺寸DC2或细胞图像面积SC2，计算获得细胞实际尺寸DC1或细胞实际面积SC1；DC1＝DC2/A，SC1＝SC2/A。
用于细胞分类的一种细胞分析方法的一个实施例中，上述获得的细胞实际尺寸DC1或细胞实际面积SC1；按照细胞实际尺寸DC1或细胞实际面积SC1的大小区间进行细胞分类。各种不同的教科书或其他参考书中，有用于细胞分类的的细胞直径范围数据。上述获得的细胞实际尺寸获得后，可根据细胞尺寸对应的数据分类将细胞归类。
用于细胞分类的一种细胞分析方法的一个实施例中，其所基于的显微图像和上述实施例中相同；在同一显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2，获取细胞图像尺寸DC2或细胞图像面积SC2；依据细胞图像尺寸DC2和参比粒子图像尺寸DR2的大小关系，或依据细胞图像面积SC2和参比粒子图像面积SR2的大小关系，进行细胞分类。
用于细胞分类的一种细胞分析方法的一个实施例中，将细胞图像尺寸DC2小于等于参比粒子图像尺寸DR2的细胞分类为第一类细胞，即DC2≤DR2的细胞分类为第一类细胞；将细胞图像尺寸DC2大于参比粒子图像尺寸DR2，且细胞图像尺寸DC2小于等于两倍参比粒子图像尺寸DR2的细胞分类为第二类细胞，即1DR2＜DC2≤2DR2的细胞分类为第二类细胞；将细胞图像尺寸DC2大于两倍参比粒子图像尺寸DR2的细胞分类为第三类细胞，即2DR2＜DC2的细胞分类为第三类细胞。
用于细胞分类的一种细胞分析方法的一个实施例中，将细胞图像面积SC2小于等于参比粒子图像面积SR2的细胞分类为第一类细胞，即SC2≤SR2的细胞分类为第一类细胞；将细胞图像面积SC2大于参比粒子图像面积SR2，且细胞图像面积SC2小于等于两倍参比粒子图像面积SR2的细胞分类为第二类细胞，即1SR2＜SC2≤2SR2的细胞分类为第二类细胞；将细胞图像面积SC2大于两倍参比粒子图像面积SR2的细胞分类为第三类细胞，即2SR2＜SC2的细胞分类为第三类细胞。
在一些实施例中，选择实际直径尺寸为5um(微米)的参比粒子；用于细胞分类。从显微图像中，获取显微图像中各细胞的直径数据，按照参比粒子图像尺寸DR2和细胞图像尺寸DC2之间的大小关系进行细胞分类，或按照或参比粒子图像面积SR2和细胞图像面积SC2之间的大小关系进行细胞分类。DC2≤DR2的细胞分类为第一类细胞；1DR2＜DC2≤2DR2的细胞分类为第二类细胞；2DR2＜DC2的细胞分类为第三类细胞。若细胞悬浮液样品中包括人身体液体样本是血液样本，则第一类细胞可以是血小板，第二类细胞可以是红细胞，第三类细胞可以是白细胞。当然不同的生物体其样本中的细胞大小不同，可以根据实际应用场景，灵活选择参比粒子的大小。
如图6所示，细胞实际尺寸表格。表格中的数据是AI图像识别系统，基于系统中的比例尺，与显微图像中每个细胞直径维度上所占像素点的多少获得的。其中用的样本是猫血液。根据《犬猫血液学手册》参考标准中给出的红细胞(RBC)尺寸范围是6.0um至7.0um；白细胞(WBC)尺寸范围是9.0um至20.0um；血小板(PLT)尺寸范围是2.2um至2.7um。
从图6中获得的数据如表格所示，根据表格中的数据即可获得不同细胞的分类计数结果：图片中细胞总数120个；红细胞(RBC)116个，白细胞(WBC)1个，血小板(PLT)13个。
也可以根据上述不同类细胞和参比粒子的尺寸关系进行细胞计数。
显然利用参比粒根据大小关系进行计数，更为简便，无需关注每个细胞的具体尺寸，只需关注相对尺寸大小关系即可进行细胞分类。对不同的细胞分类场景可以选择不同尺寸大 小的参比粒子即可。
用于获取显微图像中的细胞数量的一种细胞分析方法的实施例中，其所基于的显微图像和上述实施例中的相同；在显微图像中，获取细胞图像尺寸DC2或细胞图像面积SC2；在显微图像中，获取所有细胞占据面积ASC2；根据所有细胞占据面积ASC2和细胞图像尺寸DC2，计算获取显微图像中的细胞数量GC；或根据所有细胞占据面积ASC2和细胞图像面积SC2，计算获取显微图像中的细胞数量GC。显微图像中的细胞数量GC的计算公式可以是GC＝ASC2/SC2，也可以是GC＝ASC2/(DC2×DC2)，还可以是GC＝ASC2×π/(4×DC2×DC2)。
用于获取显微图像中的参比粒子数量的一种细胞分析方法的实施例中，其所基于的显微图像和上述实施例中的相同；在显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2；在所述显微图像中，获取所有参比粒子占据面积ASR2；根据所有参比粒子占据面积ASR2和参比粒子图像尺寸DR2，计算获取显微图像中的参比粒子数量GR；或根据所有参比粒子占据面积ASR2和参比粒子图像面积SR2，计算获取显微图像中的参比粒子数量GR。显微图像中的参比粒子数量GR的计算公式可以是GR＝ASR2/SR2，也可以是GR＝ASR2/(DR2×DR2)，还可以是GR＝ASR2×π/(4×DR2×DR2)。
用于细胞悬浮液样品的定量的一种定量方法的实施例中，用于计算获取显微图像成像对应的细胞悬浮液样品体积，其所基于的显微图像和上述实施例中的相同；获取显微图像中的参比粒子数量GR；参比粒子在细胞悬浮液样品中的浓度RC已知；获取显微图像成像对应的细胞悬浮液样品体积VM＝GR/RC。参比粒子在细胞悬浮液样品中的浓度RC单位为个/ml，即个每毫升。
以犬新鲜EDTA.K 2静脉抗凝全血为样本，选择材质为Fe 3O 4(四氧化三铁)，形状为圆球形，直径为3.0um，浓度为2.15×10 9个/ml的粒子作为本实施例的参比粒子。取10.0ul充分混匀的血液样本以及10.0ul包括参比粒子的原始参比粒子溶液加入980.0ul染色液中，充分混匀后，将混合液图加入观察平铺装置中，并置于显微成像系统中一次获取350张显微图片。
基于显微图像获取单元，获取到的350张图片中的参比粒子数量GR＝31605个，由“参比粒子原始浓度×加入试剂中的体积×VM＝获取显微图像中的参比粒子数量GR”,则VM＝31605/(2.15×10 9×0.01)＝1.47×10 -3ml。参比粒子原始浓度是指参比粒子在原始参比粒子溶液中的浓度，单位是个/ml。
用于获取细胞悬浮液样品中的细胞浓度的一种细胞分析方法的实施例中，基于上述获得显微图像成像对应的细胞悬浮液样品体积VM；获取显微图像中的细胞数量GC；根据显微 图像中的细胞数量GC和细胞悬浮液样品体积VM，计算获取细胞悬浮液样品中的细胞浓度CC。细胞浓度CC的计算公式是CC＝GC/VM。
以犬新鲜EDTA.K 2静脉抗凝全血为样本，选择材质为Fe 3O 4(四氧化三铁)，形状为圆球形，直径为3.0um，浓度为2.15×10 9个/ml的粒子作为本实施例的参比粒子。取10.0ul充分混匀的血液样本以及10.0ul的包括参比粒子的原始参比粒子溶液加入980.0ul染色液中，充分混匀后，将混合液图加入观察平铺装置中，并置于显微成像系统中一次获取350张显微图片。
基于本实施例体系，显微图像获取单元获取到的350张图片中的细胞数量GC＝103600个，基于上述实施例获得显微图像成像对应的细胞悬浮液样品体积VM＝1.47×10 -3ml；由细胞浓度CC＝GC/VM公式，计算CC＝103600/1.47×10 -3＝7.04××10 7个/ml；用于获取原始的身体液体样本中的细胞浓度的一种细胞分析方法的实施例中，基于上述获得细胞悬浮液样品中的细胞浓度CC；制备细胞悬浮液样品时，原始的身体液体样本的稀释比率X已知；原始的身体液体样本中的细胞浓度CCF＝CC/X。
以犬新鲜EDTA.K 2静脉抗凝全血为样本，选择材质为Fe 3O 4(四氧化三铁)，形状为圆球形，直径为3.0um，浓度为2.15×10 9个/ml的粒子作为本实施例的参比粒子。取10.0ul充分混匀的血液样本以及10.0ul的包括参比粒子的原始参比粒子溶液加入980.0ul染色液中，充分混匀后，将混合液图加入观察平铺装置中，并置于显微成像系统中一次获取350张显微图片。
基于本实施例体系，原始的身体液体样本的稀释比率X＝0.01；基于上述实施例计算得CC＝7.04××10 7个/ml,所以，CCF＝CC/X＝7.04×10 7/0.01＝7.04×10 9(个/ml)。
用于获取原始的身体液体样本中的细胞浓度的一种细胞分析方法的实施例中，其所基于的显微图像和上述实施例中的相同；在显微图像中，获取所有细胞占据面积ASC2；在显微图像中，获取细胞图像尺寸DC2或细胞图像面积SC2；在显微图像中，获取所有参比粒子占据面积ASR2；在显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2；原始参比粒子溶液的浓度CRF已知；制备细胞悬浮液样品时，加入原始参比粒子溶液体积VR已知；制备细胞悬浮液样品时，原始的身体液体样本细胞浓度CCF未知；制备细胞悬浮液样品时，加入原始的身体液体样本的体积V1已知；依据ASC2/ASR2＝CCF×V1×DC2×DC2/(CRF×VR×DR2×DR2)，求得原始的身体液体样本的细胞浓度CCF。或依据ASC2/ASR2＝CCF×V1×SC2/(CRF×VR×SR2)，求得原始的身体液体样本的细胞浓度CCF。
以犬新鲜EDTA.K 2静脉抗凝全血为样本，选择材质为Fe 3O 4(四氧化三铁)，形状为圆 球形，直径为3.0um，浓度为2.15×10 9个/ml的粒子作为本实施例的参比粒子。取10.0ul充分混匀的血液样本以及10.0ul的包括参比粒子的原始参比粒子溶液加入980.0ul染色液中，充分混匀后，将混合液图加入观察平铺装置中，并置于显微成像系统中一次获取350张显微图片。
基于显微图像获取单元，获取所有细胞占据面积ASC2＝38.5×10 -3cm 2；获取单一细胞的细胞图像尺寸DC2＝6.1×10 -4cm；获取所有参比粒子占据面积ASR2＝2.7×10 -3cm 2；获取单一参比粒子的参比粒子图像尺寸DR2＝3.0×10 -4cm；已知原始参比粒子溶液的浓度为CRF＝2.15×10 9个/ml；原始参比粒子溶液体积Va与原始样本液体积V1的加入量相等，均为10ul。
由公式：ASC2/ASR2＝CCF×V1×DC2×DC2/(CRF×VR×DR2×DR2)可知CCF＝ASC2×CRF×Va×DR2×DR2/(ASR2×V1×DC2×DC2)；即CCF＝38.5×10 -3×2.15×10 12×0.01×10 -3×3.0×10 -4×3.0×10 -4/(2.7×10 -3×0.01×10 -3×6.1×10 -4×6.1×10 -4)＝7.41×10 9(个/ml)。
或者，基于显微图像获取单元，获取所有细胞占据面积ASC2＝38.5×10 -3cm 2；获取单一细胞的面积SC2＝117.61×10 -8cm 2；获取所有参比粒子占据面积ASR2＝2.7×10 -3cm 2；获取单一参比粒子的参比粒子图像尺寸SR2＝29.59×10 -8cm 2；已知原始参比粒子溶液的浓度为CRF＝2.15×10 9个/ml；原始参比粒子溶液体积Va与原始样本液体积V1的加入量相等，均为10ul。
由公式：ASC2/ASR2＝CCF×V1×SC2/(CRF×VR×SR2)可知CCF＝ASC2×CRF×VR×SR2/(ASR2×V1×SC2)＝38.5×10 -3×2.15×10 9×0.01×10 -3×29.59×10 -8/(2.7×10 -3×0.01×10 -3×117.61×10 -8)＝7.71×10 9(个/ml)。
用于获取原始的身体液体样本中的细胞浓度的一种细胞分析方法的实施例中，其所基于的显微图像和上述实施例中的相同；在显微图像中，获取所有细胞个数GC；在显微图像中，获取参比粒子个数GR；原始参比粒子溶液的浓度CRF已知；制备细胞悬浮液样品时，加入原始参比粒子溶液体积VR已知；制备细胞悬浮液样品时，原始的身体液体样本浓度CCF未知；制备细胞悬浮液样品时，加入原始的身体液体样本体积V1已知；根据已知的CRF、VR、V1、GR、GC，以及公式CRF×VR/(CCF×V1)＝GR/GC，计算获得CCF。
以犬新鲜EDTA.K 2静脉抗凝全血为样本，选择材质为Fe 3O 4(四氧化三铁)，形状为圆球形，直径为3.0um，浓度为2.15×10 9个/ml的粒子作为本实施例的参比粒子。取10.0ul充分混匀的血液样本以及10.0ul的包括参比粒子的原始参比粒子溶液加入980.0ul染色液中，充 分混匀后，将混合液图加入观察平铺装置中，并置于显微成像系统中一次获取350张显微图片。
基于显微图像获取单元，获取到的350张图片中的细胞数量GC＝103600；获取参比粒子数量GR＝31605；已知原始参比粒子溶液体积Va与原始样本液体积V1的加入量相等，均为10ul；已知粒子浓度CRa＝2.15×10 9个/ml；由公式：CRF×VR/(CCF×V1)＝GR/GC可得CCF＝GC×CRF×VR/GR；即CCF＝103600×2.15×10 9×0.01×10 -3/(29750×0.01×10 -3)＝7.49×10 9(个/ml)；在上述用于获取细胞悬浮液样品中的细胞浓度的一种细胞分析方法或定量方法的实施例中，获取显微图像中的细胞数量GC的方法是：在所述显微图像中，获取细胞图像尺寸DC2或细胞图像面积SC2；在所述显微图像中，获取所有细胞占据面积ASC2；根据所有细胞占据面积ASC2和细胞图像尺寸DC2，计算获取显微图像中的细胞数量GC；或根据所有细胞占据面积ASC2和细胞图像面积SC2，计算获取显微图像中的细胞数量GC。
在上述用于获取细胞悬浮液样品中的细胞浓度的一种细胞分析方法或定量方法的实施例中，获取显微图像中的细胞数量GC的方法是：根据细胞形态或细胞大小直接识别出细胞后，对所有细胞计数获得。
用于细胞悬浮液样品的定量的一种细胞分析方法或定量方法的实施例中，获取显微图像中的参比粒子数量GR的方法是：在显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2；在显微图像中，获取所有参比粒子占据面积ASR2；根据所有参比粒子占据面积ASR2和参比粒子图像尺寸DR2，计算获取显微图像中的参比粒子数量GR；或根据所有参比粒子占据面积ASR2和参比粒子图像面积SR2，计算获取显微图像中的参比粒子数量GR。
用于细胞悬浮液样品的定量的一种细胞分析方法或定量方法的实施例中，获取显微图像中的参比粒子数量GR的方法是：根据参比粒子形态或参比粒子大小直接识别出参比粒子后，对所有参比粒子计数获得。
测量显微图像中多个细胞图像尺寸，取多个细胞图像尺寸的统计数值用作细胞图像尺寸DC2；或测量显微图像中多个细胞图像面积，取多个细胞图像尺寸的统计数值用作细胞图像面积SC2；或测量显微图像中单一细胞的图像尺寸或面积，用作细胞图像尺寸DC2或细胞图像面积SC2；或测量多幅显微图像中每一幅显微图像中的单一细胞的图像尺寸或面积，用作细胞图像尺寸DC2或细胞图像面积SC2；或测量多幅显微图像中每一幅图像中的多个细胞图像尺寸或面积，取每一幅图像中的多个细胞图像尺寸的统计数值用作该幅图像的细胞图像尺寸，取多幅显微图像的细胞图像尺寸的统计数值用作细胞图像尺寸DC2或细胞图像面积 SC2。
即细胞图像尺寸DC2或细胞图像面积SC2可以有多种来源，其中之一是单幅显微图像中的单一的具有尺寸代表性的细胞图像尺寸；其中之二是多幅显微图像中多个单一的具有尺寸代表性的细胞图像尺寸的统计数值；其中之三是单幅显微图像中的多个细胞图像尺寸的统计数值，统计数值包括取平均数，统计数值也包括其他统计方式，如按照分布概率或置信区间进行统计处理；其中之四是在第三种的基础上，取多幅显微图像中各单幅显微图像中多个细胞图像尺寸的统计数值，再取统计数值。
参比粒子的图像尺寸DR2或图像面积SR2也采用上述方法获得。
如图1所示，细胞分析系统的一个实施例中，包括分析用显微图像获取单元和显微图像分析单元；分析用显微图像获取单元，获取用于细胞分析的显微图像；显微图像分析单元利用上述细胞分析方法，基于分析用显微图像获取单元获取的显微图像完成细胞分析。
如图2所示，定量系统的一个实施例中，包括定量分析显微图像获取单元和定量分析单元；定量分析显微图像获取单元用于获取用于定量分析的显微图像；定量分析单元利用上述定量方法，基于定量分析显微图像获取单元获取的显微图像，计算获取显微图像成像对应的细胞悬浮液样品体积。
如图1和图2中的细胞分析系统或定量系统中，都可以包括细胞悬浮液样品成像子系统。细胞悬浮液样品成像子系统向分析用显微图像获取单元或量分析显微图像获取单元提供显微图像。分析用显微图像获取单元和细胞悬浮液样品成像子系统之间可有线电连接或无线电连接获取显微图像信息；同样定量分析显微图像获取单元和细胞悬浮液样品成像子系统之间可有线电连接或无线电连接获取显微图像信息。
在一些附图中未显示的一种细胞悬浮液样品成像子系统实施例中，细胞悬浮液样品中包括细胞和参比粒子；载体，用于承载细胞悬浮液样品；载体包括承载面；细胞悬浮液样品进入载体后，细胞悬浮液样品中的细胞和参比粒子沉降在承载面上形成包括细胞和参比粒子的观察层；显微图像获取单元，用于获取包括细胞和参比粒子的观察层的至少一幅图像。显微图像获取单元包括具有成像功能的装置，如CCD成像装置或其他能数字化记录或呈现显微图像的装置。这些装置能将显微镜获得的显微图像拍摄记录下来形成电子文件。显微图像获取单元包括荧光显微镜或普通光学显微镜。
参比粒子参与成像后，参比粒子可以用作后续计算的数量标尺，简化了计算逻辑和计算的准确性。在固定体积的细胞悬浮液样品中，细胞悬浮液样品中包括了试剂，样本和参比粒子，三者充分混匀后，参比粒子在观察层的平铺、分布规律与待测样本中的细胞一致，可 直接通过计数显微图片中参比粒子与细胞的之间的尺寸、面积或数量关系，来计算原始样本中的细胞浓度或数量，无需考虑其它因素，如观察区的容积和面积；即承载面所处空间即细胞核参比粒子平铺区域的深度、视野的大小对成像以及后续计算的影响大大降低。
参比粒子参与成像后，利用成像图片进行细胞计数时，提升了计数准确性。在传统计数逻辑中，更多依赖于计数板的加工精度，尤其是平铺、分布区域体积。平铺、分布区域体积的工艺误差直接影响细胞的数量，从而计数结果；而加入内标的参比粒子，使细胞计数逻辑已与平铺、分布区域体积的体积无关。
参比粒子参与成像后，可利用参比粒子作为自动对焦参照物，校正成像质量；参比粒子具有尺寸均一性，在一个样本的检测过程中，会涉及多个视野的观察与计数，此时以具有标准尺寸的参比粒子，作为对焦参考点，实现图像对焦的均一性，从而增强图片质量，提升结果准确性。
以上所述仅为本申请的实施例，并非因此限制本申请的专利范围，凡是利用发明说明书及附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本申请的专利保护范围内。

Claims (21)

  1. 一种细胞分析方法，用于获取细胞悬浮液样品中细胞实际尺寸，其特征在于，
    基于显微图像；所述显微图像是细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层的部分或全部的至少一幅显微图像；细胞悬浮液样品中的参比粒子实际尺寸DR1或参比粒子实际面积SR1已知；
    在同一显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2，获取细胞图像尺寸DC2或细胞图像面积SC2；
    根据参比粒子实际尺寸DR1或参比粒子实际面积SR1、参比粒子图像尺寸DR2或参比粒子图像面积SR2、细胞图像尺寸DC2或细胞图像面积SC2，计算获得细胞实际尺寸DC1或细胞实际面积SC1。
  2. 一种细胞分析方法，用于细胞分类，其特征在于，
    基于权利要求1获得的细胞实际尺寸DC1或细胞实际面积SC1；按照细胞实际尺寸DC1或细胞实际面积SC1的大小区间进行细胞分类。
  3. 一种细胞分析方法，用于细胞分类，其特征在于，
    基于显微图像；所述显微图像是细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层的部分或全部的至少一幅显微图像；
    在同一显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2，获取细胞图像尺寸DC2或细胞图像面积SC2；
    依据细胞图像尺寸DC2和参比粒子图像尺寸DR2的大小关系，进行细胞分类；
    或依据细胞图像面积SC2和参比粒子图像面积SR2的大小关系，进行细胞分类。
  4. 根据权利要求3所述细胞分析方法，其特征在于，
    将细胞图像尺寸DC2小于等于参比粒子图像尺寸DR2的细胞分类为第一类细胞，即DC2≤DR2的细胞分类为第一类细胞；
    或将细胞图像面积SC2小于等于参比粒子图像面积SR2的细胞分类为第一类细胞，即SC2≤SR2的细胞分类为第一类细胞；
    将细胞图像尺寸DC2大于参比粒子图像尺寸DR2，且细胞图像尺寸DC2小于等于两倍参比粒子图像尺寸DR2的细胞分类为第二类细胞，即1DR2＜DC2≤2DR2的细胞分类为第二类细胞；
    或将细胞图像面积SC2大于参比粒子图像面积SR2，且细胞图像面积SC2小于等于两倍参比粒子图像面积SR2的细胞分类为第二类细胞，即1SR2＜SC2≤2SR2的细胞分类为第二类细胞；
    将细胞图像尺寸DC2大于两倍参比粒子图像尺寸DR2的细胞分类为第三类细胞，即2DR2＜DC2的细胞分类为第三类细胞；
    或将细胞图像面积SC2大于两倍参比粒子图像面积SR2的细胞分类为第三类细胞，即2SR2＜SC2的细胞分类为第三类细胞。
  5. 一种细胞分析方法，用于获取显微图像中的细胞数量，其特征在于，
    基于显微图像；所述显微图像是细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层的部分或全部的至少一幅显微图像；
    在所述显微图像中，获取细胞图像尺寸DC2或细胞图像面积SC2；
    在所述显微图像中，获取所有细胞占据面积ASC2；
    根据所有细胞占据面积ASC2和细胞图像尺寸DC2，计算获取显微图像中的细胞数量GC；
    或根据所有细胞占据面积ASC2和细胞图像面积SC2，计算获取显微图像中的细胞数量GC。
  6. 一种细胞分析方法，用于获取显微图像中的参比粒子数量，其特征在于，
    基于显微图像；所述显微图像是细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层的部分或全部的至少一幅显微图像；
    在所述显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2；在所述显微图像中，获取所有参比粒子占据面积ASR2；
    根据所有参比粒子占据面积ASR2和参比粒子图像尺寸DR2，计算获取显微图像中的参比粒子数量GR；
    或根据所有参比粒子占据面积ASR2和参比粒子图像面积SR2，计算获取显微图像中的参比粒子数量GR。
  7. 一种定量方法，用于细胞悬浮液样品的定量，即计算获取显微图像成像对应的细胞悬浮液样品体积，其特征在于，
    基于显微图像；所述显微图像是细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层的部分或全部的至少一幅显微图像；
    获取显微图像中的参比粒子数量GR；
    参比粒子在细胞悬浮液样品中的浓度RC已知；
    获取显微图像成像对应的细胞悬浮液样品体积VM＝GR/RC。
  8. 根据权利要求7所述定量方法，其特征在于，
    获取显微图像中的参比粒子数量GR的方法是：
    在所述显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2；
    在所述显微图像中，获取所有参比粒子占据面积ASR2；
    根据所有参比粒子占据面积ASR2和参比粒子图像尺寸DR2，计算获取显微图像中的参比粒子数量GR；
    或根据所有参比粒子占据面积ASR2和参比粒子图像面积SR2，计算获取显微图像中的参比粒子数量GR。
  9. 根据权利要求7所述定量方法，其特征在于，
    获取显微图像中的参比粒子数量GR的方法是：
    根据参比粒子形态或参比粒子大小直接识别出参比粒子后，对所有参比粒子计数获得。
  10. 一种细胞分析方法，用于获取细胞悬浮液样品中的细胞浓度，其特征在于，
    基于权利要求7获得显微图像成像对应的细胞悬浮液样品体积VM；
    获取显微图像中的细胞数量GC；
    根据显微图像中的细胞数量GC和细胞悬浮液样品体积VM，计算获取细胞悬浮液样品中的细胞浓度CC，CC＝GC/VM。
  11. 根据权利要求10所述细胞分析方法，其特征在于，
    获取显微图像中的细胞数量GC的方法是：
    在所述显微图像中，获取细胞图像尺寸DC2或细胞图像面积SC2；
    在所述显微图像中，获取所有细胞占据面积ASC2；
    根据所有细胞占据面积ASC2和细胞图像尺寸DC2，计算获取显微图像中的细胞数量GC；
    或根据所有细胞占据面积ASC2和细胞图像面积SC2，计算获取显微图像中的细胞数量GC。
  12. 根据权利要求10所述细胞分析方法，其特征在于，
    获取显微图像中的细胞数量GC的方法是：
    根据细胞形态或细胞大小直接识别出细胞后，对所有细胞计数获得。
  13. 一种细胞分析方法，用于获取原始的身体液体样本中的细胞浓度，其特征在于，
    基于权利要求10获得的细胞悬浮液样品中的细胞浓度CC；
    制备细胞悬浮液样品时，原始的身体液体样本的稀释比率X已知；
    原始的身体液体样本中的细胞浓度CCF＝CC/X。
  14. 一种细胞分析方法，用于获取原始的身体液体样本中的细胞浓度，其特征在于，
    基于显微图像；所述显微图像是细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层的部分或全部的至少一幅显微图像；
    在显微图像中，获取所有细胞占据面积ASC2；
    在显微图像中，获取细胞图像尺寸DC2或细胞图像面积SC2；
    在显微图像中，获取所有参比粒子占据面积ASR2；
    在显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2；
    原始参比粒子溶液的浓度CRF已知；
    制备细胞悬浮液样品时，加入原始参比粒子溶液体积VR已知；
    制备细胞悬浮液样品时，原始的身体液体样本细胞浓度CCF未知；
    制备细胞悬浮液样品时，加入原始的身体液体样本的体积V1已知；
    依据已知的ASC2、ASR2、V1、DC2、CRF、VR、DR2，获取原始的身体液体样本的细胞浓度CCF；
    或依据ASC2、ASR2、V1、SC2、CRF、VR、SR2，获取原始的身体液体样本的细胞浓度CCF。
  15. 一种细胞分析方法，用于获取原始的身体液体样本中的细胞浓度，其特征在于，
    基于显微图像；所述显微图像是细胞悬浮液样品中的细胞和参比粒子沉降在载体的承载面上形成包括细胞和参比粒子的观察层的部分或全部的至少一幅显微图像；
    在显微图像中，获取所有细胞个数GC；
    在显微图像中，获取参比粒子个数GR；
    原始参比粒子溶液的浓度CRF已知；
    制备细胞悬浮液样品时，加入原始参比粒子溶液体积VR已知；
    制备细胞悬浮液样品时，原始的身体液体样本浓度CCF未知；
    制备细胞悬浮液样品时，加入原始的身体液体样本体积V1已知；
    根据已知的CRF、VR、V1、GR、GC计算获得CCF。
  16. 根据权利要求15所述细胞分析方法，其特征在于，
    获取显微图像中的细胞数量GC的方法是：
    在所述显微图像中，获取细胞图像尺寸DC2或细胞图像面积SC2；
    在所述显微图像中，获取所有细胞占据面积ASC2；
    根据所有细胞占据面积ASC2和细胞图像尺寸DC2，计算获取显微图像中的细胞数量GC；
    或根据所有细胞占据面积ASC2和细胞图像面积SC2，计算获取显微图像中的细胞数量GC。
  17. 根据权利要求15所述细胞分析方法，其特征在于，
    获取显微图像中的细胞数量GC的方法是：
    根据细胞形态或细胞大小直接识别出细胞后，对所有细胞计数获得。
  18. 根据权利要求15所述细胞分析方法，其特征在于，
    获取显微图像中的参比粒子数量GR的方法是：
    在所述显微图像中，获取参比粒子图像尺寸DR2或参比粒子图像面积SR2；
    在所述显微图像中，获取所有参比粒子占据面积ASR2；
    根据所有参比粒子占据面积ASR2和参比粒子图像尺寸DR2，计算获取显微图像中的参比粒子数量GR；
    或根据所有参比粒子占据面积ASR2和参比粒子图像面积SR2，计算获取显微图像中的参比粒子数量GR。
  19. 根据权利要求15所述细胞分析方法，其特征在于，
    获取显微图像中的参比粒子数量GR的方法是：
    根据参比粒子形态或参比粒子大小直接识别出参比粒子后，对所有参比粒子计数获得。
  20. 一种细胞分析系统，其特征在于，
    包括分析用显微图像获取单元和显微图像分析单元；
    分析用显微图像获取单元，获取用于细胞分析的显微图像；
    显微图像分析单元利用上述权利要求1至6，或权利要求10至19中任意一项所述的细胞分析方法，基于分析用显微图像获取单元获取的显微图像完成细胞分析。
  21. 一种定量系统，其特征在于，
    包括定量分析显微图像获取单元和定量分析单元；
    定量分析显微图像获取单元，获取用于定量分析的显微图像；
    定量分析单元利用上述权利要求7至9中任意一项所述的定量方法，基于定量分析显微图像获取单元获取的显微图像，计算获取显微图像成像对应的细胞悬浮液样品体积。
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20010041343A1 (en) * 1999-05-04 2001-11-15 Pankowsky Dan A. Products and methods for single parameter and multiparameter phenotyping of cells
CN103443625A (zh) * 2010-10-21 2013-12-11 耐克思乐生物科学有限责任公司 成像细胞仪的内部聚焦参考珠
CN107904278A (zh) * 2017-12-25 2018-04-13 北昊干细胞与再生医学研究院有限公司 检测药物对细胞增殖影响的方法
US20190178876A1 (en) * 2016-07-29 2019-06-13 Streck, Inc. Suspension composition for hematology analysis control
US20190331581A1 (en) * 2017-01-31 2019-10-31 Fujifilm Corporation Cell culture apparatus, imaging unit, and culture monitoring method
US20190331689A1 (en) * 2018-04-27 2019-10-31 Deutsches Rheuma-Forschungszentrum Berlin Functionalized metal-labeled beads for mass cytometry

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5039487A (en) * 1987-12-22 1991-08-13 Board Of Regents, The University Of Texas System Methods for quantifying components in liquid samples
US8883491B2 (en) * 2008-04-09 2014-11-11 Nexcelom Bioscience Llc Systems and methods for counting cells and biomolecules
MX362545B (es) * 2013-02-18 2019-01-24 Theranos Ip Co Llc Analisis de imagen y medicion de muestras biologicas.
IL227276A0 (en) * 2013-07-01 2014-03-06 Parasight Ltd A method and system for obtaining a monolayer of cells, for use specifically for diagnosis

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20010041343A1 (en) * 1999-05-04 2001-11-15 Pankowsky Dan A. Products and methods for single parameter and multiparameter phenotyping of cells
CN103443625A (zh) * 2010-10-21 2013-12-11 耐克思乐生物科学有限责任公司 成像细胞仪的内部聚焦参考珠
US20190178876A1 (en) * 2016-07-29 2019-06-13 Streck, Inc. Suspension composition for hematology analysis control
US20190331581A1 (en) * 2017-01-31 2019-10-31 Fujifilm Corporation Cell culture apparatus, imaging unit, and culture monitoring method
CN107904278A (zh) * 2017-12-25 2018-04-13 北昊干细胞与再生医学研究院有限公司 检测药物对细胞增殖影响的方法
US20190331689A1 (en) * 2018-04-27 2019-10-31 Deutsches Rheuma-Forschungszentrum Berlin Functionalized metal-labeled beads for mass cytometry

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