A method and apparatus for identifying red blood cell fragments

Abstract

The application discloses a red blood cell fragment identification method and device. The red blood cell fragment identification method comprises the following steps: obtaining a three-dimensional cell scatter diagram constituted by a forward scattering light signal, a side scattering light signal and a fluorescence signal of a cell particle in a blood sample; obtaining a two-dimensional cell scatter diagram constituted by a forward scattering light signal and a fluorescence signal according to the three-dimensional cell scatter diagram and a rotation processing, wherein a first coordinate axis of the two-dimensional cell scatter diagram is a comprehensive light signal, and an overlap rate between a positive projection of a red blood cell region and a platelet region in the two-dimensional cell scatter diagram on the first coordinate axis is lower than a threshold value; performing a transmission processing on the two-dimensional cell scatter diagram with the first coordinate axis to obtain a target histogram; determining a red blood cell fragment region in the target histogram, and obtaining a red blood cell fragment particle number from the red blood cell fragment region. In the above manner, the probability of misidentification can be effectively reduced, and the identification accuracy is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of blood detection, in particular to a method and device for identifying red cell fragments. BACKGROUND

[0002] In the field of clinical medicine, red cell fragments (FRC) can be used as a judgment index for diseases such as disseminated intravascular coagulation, megaloblastic anemia, hemolytic anemia, cardiogenic hemolytic anemia, and malignant tumor. In the detection of blood samples, it is often necessary to detect red cell fragments in blood samples for doctors to refer to. The proportion of red cell fragments in peripheral blood red cells of normal people should be less than 1%, therefore, the test of red cell fragments has a high requirement for accuracy.

[0003] In recent years, blood cytometers using the principle of flow cytometry to count and classify blood cells have been developed. The blood cytometers mainly use dyes to stain blood cells, detect two-dimensional cell scatter plots composed of forward scattering light and fluorescence information of the cells, and obtain the number of red cell fragment particles and the proportion between red cell fragments and red blood cells based on the scattering light and fluorescence information.

[0004] However, the present inventors have found in long-term research and development that, due to a large amount of overlap in the distribution area of each cell, other cells such as platelets and small red blood cells may exist in the preset area of red cell fragments, and the probability of misrecognition is relatively large. When the test task of red cell fragments is directly performed through a two-dimensional cell scatter plot, the result obtained has a large error compared with manual microscopic examination. SUMMARY

[0005] The technical problem solved by the present application is to provide a method and device for identifying red cell fragments, which can effectively reduce the probability of misrecognition and improve the accuracy of identification.

[0006] To solve the above technical problem, one technical solution adopted by the present application is to provide a method for identifying red cell fragments, comprising: obtaining a three-dimensional cell scatter plot composed of forward scattering light signals, side scattering light signals, and fluorescence signals of cell particles in a blood sample; obtaining a two-dimensional cell scatter plot composed of forward scattering light signals and fluorescence signals according to the three-dimensional cell scatter plot and rotation processing, wherein a first coordinate axis of the two-dimensional cell scatter plot is a comprehensive light signal, and an overlap rate between the positive projections of red blood cell regions and platelet regions in the two-dimensional cell scatter plot on the first coordinate axis is lower than a threshold value; performing transmission processing on the two-dimensional cell scatter plot with the first coordinate axis to obtain a target histogram; determining a red cell fragment region in the target histogram, and obtaining a number of red cell fragment particles from the red cell fragment region.

[0007] The step of obtaining the two-dimensional cell scatter diagram composed of the forward scattering light signal and the fluorescence signal according to the three-dimensional cell scatter diagram and the rotation processing includes: rotating the three-dimensional cell scatter diagram, and obtaining the two-dimensional cell scatter diagram according to the three-dimensional cell scatter diagram after rotation; or obtaining a two-dimensional initial cell scatter diagram composed of the forward scattering light signal and the fluorescence signal before rotation according to the three-dimensional cell scatter diagram; and rotating the two-dimensional initial cell scatter diagram to obtain the two-dimensional cell scatter diagram.

[0008] The first direction of the three-dimensional cell scatter diagram represents the fluorescence signal in the blood sample, the second direction represents the forward scattering light signal in the blood sample, and the third direction represents the side scattering light signal in the blood sample; the step of rotating the three-dimensional cell scatter diagram includes: rotating the three-dimensional cell scatter diagram counterclockwise around the third direction by a first angle; or the step of rotating the two-dimensional initial cell scatter diagram to obtain the two-dimensional cell scatter diagram includes: rotating the two-dimensional initial cell scatter diagram counterclockwise around the third direction by a first angle.

[0009] Before the step of rotating the three-dimensional cell scatter diagram counterclockwise around the third direction by a first angle or before the step of rotating the two-dimensional initial cell scatter diagram counterclockwise around the third direction by a first angle, the method further includes: obtaining a first included angle between the platelet region in the three-dimensional cell scatter diagram and the first direction; and determining the first angle by using the first included angle, wherein the first included angle is inversely related to the first angle.

[0010] The sum of the first included angle and the first angle is 90 degrees.

[0011] Before the step of obtaining the first included angle between the platelet region in the three-dimensional cell scatter diagram and the first direction, the method further includes: rotating the three-dimensional cell scatter diagram counterclockwise around the second direction by a second angle, so that at least part of the side scattering light signal is superimposed on the forward scattering light signal.

[0012] The second angle is between 0 degrees and 90 degrees.

[0013] The step of determining the red blood cell fragment region in the target histogram includes: obtaining peak value information of a red blood cell region and a platelet region in the target histogram; determining a first boundary line of the red blood cell fragment region by using the peak value information of the red blood cell region, and determining a second boundary line of the red blood cell fragment region by using the peak value information of the platelet region.

[0014] The step of obtaining the number of red blood cell fragment particles from the red blood cell fragment region comprises: obtaining the number of red blood cell particles in the red blood cell region in the target histogram; and taking the ratio of the number of red blood cell fragment particles to the number of red blood cell particles as the red blood cell fragment particle proportion value.

[0015] To solve the above technical problems, another technical solution adopted by the present application is to provide a red blood cell fragment identification device, comprising a memory and a processor coupled to each other, the memory stores program instructions, and the program instructions are used to be executed by the processor to realize the red blood cell fragment identification method mentioned in any of the above embodiments.

[0016] Different from the prior art, the beneficial effects of the present application are: the present application provides a red blood cell fragment identification method, which converts three-dimensional data composed of forward scattering light, side scattering light and fluorescence signal into two-dimensional data through rotation processing, and then converts the two-dimensional data into one-dimensional target histogram data through transmission processing, and then accurately obtains the number of red blood cell fragment particles in the red blood cell fragment region. Through the rotation processing of the cell scatter plot, the light signals of multiple angles are integrated in the process of identifying the red blood cell fragments, solving the problem of a large number of overlaps in each cell distribution region in the prior art, effectively reducing the misidentification probability of red blood cell fragments, improving the identification accuracy, and further reducing the probability of false positive of blood test results. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor. Among them:

[0018] Figure 1 is a two-dimensional scatter plot obtained by identifying red blood cell fragments based on forward scattering light signal and fluorescence signal in the prior art;

[0019] Figure 2 is a flowchart of an embodiment of the red blood cell fragment identification method of the present application;

[0020] Figure 3 is Figure 2 is a flowchart of an embodiment before step S102 in

[0021] Figure 4 is Figure 3 is a cell scatter plot of an embodiment of steps S201-S202 in

[0022] Figure 5is Figure 2 A flowchart of an embodiment of step S104 is shown in FIG. 4.

[0023] Figure 6 is Figure 2 A target histogram of an embodiment of step S104 is shown in FIG. 5.

[0024] Figure 7 is Figure 5 A flowchart of an embodiment after step S302 is shown in FIG. 6.

[0025] Figure 8 is a frame diagram of an embodiment of the cell fragment recognition device of the present application.

[0026] Figure 9 is a structure diagram of an embodiment of the red blood cell fragment recognition device of the present application.

[0027] Figure 10 is a frame diagram of an embodiment of the computer readable storage medium of the present application. DETAILED DESCRIPTION

[0028] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present application.

[0029] In order to better understand the present application, the present embodiment will sequentially make specific explanations and descriptions on the concepts of blood sample, red blood cell, cell scatter plot, etc.

[0030] In the present embodiment, the blood sample can be a sample obtained by collecting from a human or animal body and reacting with a dye reagent, wherein the dye reagent includes a fluorescent reagent, etc. The blood sample includes various cells, such as red blood cells, white blood cells, platelets, etc.

[0031] The red blood cells can be classified from the perspective of development degree, and are specifically subdivided into mature red blood cells, reticulocytes, etc., wherein the reticulocytes refer to red blood cells that are not yet fully mature, i.e., red blood cell fragments.

[0032] In view of the difference and regional distribution characteristics of the fluorescence signal between different red blood cells and the forward scattering light signal and the side scattering light signal between different red blood cells, the cell scatter plot in the present application is a three-dimensional scatter plot established according to the forward scattering light signal, the side scattering light signal and the fluorescence signal of the blood sample. In an embodiment, the optical information of the cell particles in the sample is obtained by a blood cell analyzer, and the optical information of the collected cell particles including the forward scattering light signal, the side scattering light signal and the fluorescence signal is detected for identifying the red blood cell fragments. The forward scattering light signal can reflect the volume of the cell, and the higher the forward scattering light intensity, the larger the volume of the cell. The side scattering light signal representing the cell content is weakened due to the loss of hemoglobin in the red blood cell fragments, so the red blood cell fragments produce weak side scattering light signal.

[0033] Referring to Figure 1 , Figure 1 is a two-dimensional scatter plot obtained by identifying the red blood cell fragments based on the forward scattering light signal and the fluorescence signal in the prior art. According to the difference and regional distribution characteristics of the forward scattering light signal and the fluorescence signal of different red blood cells, the illustrated two-dimensional cell scatter plot includes a mature red blood cell region 10, a red blood cell fragment region 12 and a platelet region 14. Obviously, the red blood cell fragment region 12 in the blood sample is adjacent to the mature red blood cell region 10, and there is partial overlap, so that misidentification is likely to occur in the identification process.

[0034] Therefore, it is necessary to provide a method for identifying red blood cell fragments to effectively improve the identification accuracy.

[0035] Referring to Figure 2 , Figure 2 is a flowchart of an embodiment of the method for identifying red blood cell fragments according to the present application. Specifically, it can include the following steps:

[0036] S101: obtaining a three-dimensional cell scatter plot constituted by the forward scattering light signal, the side scattering light signal and the fluorescence signal of the cell particles in the blood sample.

[0037] Specifically, the specific content of the three-dimensional cell scatter plot of the blood sample can be referred to the related description in the above part of the present application, which will not be described here.

[0038] In the present embodiment, the three-dimensional cell scatter plot can be a scatter plot containing all cells in the blood sample, or a three-dimensional cell scatter plot containing only target cells such as red blood cells and red blood cell fragments after processing, which is not specifically limited here.

[0039] In yet another embodiment, the first direction of the three-dimensional cell scatter plot represents a fluorescent signal in the blood sample, the second direction represents a forward scattering light signal in the blood sample, and the third direction represents a side scattering light signal in the blood sample. Of course, in other embodiments, the optical signals represented by each direction of the three-dimensional cell scatter plot are not specifically limited, as long as each direction represents a different optical signal.

[0040] S102: obtaining a two-dimensional cell scatter plot composed of a forward scattering light signal and a fluorescent signal according to the three-dimensional cell scatter plot and the rotation processing, wherein a first coordinate axis of the two-dimensional cell scatter plot is a comprehensive optical signal, and an overlap rate between a positive projection of a red blood cell region and a platelet region on the first coordinate axis is lower than a threshold value.

[0041] Optionally, in the present embodiment, the rotation processing is directly performed on the data in the three-dimensional cell scatter plot, and then the three-dimensional cell scatter plot after the rotation is projected to obtain the two-dimensional cell scatter plot composed of the forward scattering light signal and the fluorescent signal. At this time, the first coordinate axis of the two-dimensional cell scatter plot comprehensively includes optical information of three angles of the fluorescent signal, the forward scattering light signal and the side scattering light signal, that is, the comprehensive optical signal is composed of the fluorescent signal, the forward scattering light signal and the side scattering light signal.

[0042] In yet another embodiment, the three-dimensional cell scatter plot is first projected to obtain a two-dimensional initial cell scatter plot composed of a forward scattering light signal and a fluorescent signal, and then the two-dimensional initial cell scatter plot is rotated to obtain a two-dimensional cell scatter plot. At this time, the first coordinate axis of the two-dimensional cell scatter plot comprehensively includes optical information of two angles of the fluorescent signal and the forward scattering light signal, that is, the comprehensive optical signal is composed of the fluorescent signal and the forward scattering light signal, and an overlap rate between a positive projection of a red blood cell region and a platelet region on the first coordinate axis is lower than a threshold value.

[0043] The threshold values mentioned in the above embodiments can be set according to the recognition accuracy, for example, set to 10%, which means that the overlap rate between the positive projection of the red blood cell region and the platelet region on the first coordinate axis is less than 10%.

[0044] Through the above embodiments, whether the rotation is performed first and then the projection or the projection is performed first and then the rotation, the three-dimensional data originally obtained can be converted into two-dimensional data, which not only comprehensively includes optical signals of multiple angles in the process of identifying red blood cell fragments, but also solves the problem of a large amount of overlap between the distribution regions of various cells in the prior art, so that the red blood cell region and the platelet region in the two-dimensional cell scatter plot are separated as much as possible.

[0045] In a specific implementation scenario, the step of rotating the three-dimensional cell scatter plot includes: rotating the three-dimensional cell scatter plot counterclockwise around the third direction by the first angle. Specifically, the third direction refers to the side scattering light signal in the blood sample, that is, the forward scattering light signal and the fluorescence signal data are rotated around the third direction while keeping the side scattering data unchanged.

[0046] In another specific implementation scenario, the step of rotating the two-dimensional initial cell scatter plot includes: rotating the two-dimensional initial cell scatter plot counterclockwise around the third direction by the first angle. Specifically, the third direction refers to the side scattering light signal in the blood sample, that is, the forward scattering light signal and the fluorescence signal are rotated around the third direction.

[0047] Through the above implementation, whether the three-dimensional cell scatter plot is directly rotated or the two-dimensional initial cell scatter plot is rotated, the two-dimensional cell scatter plot composed of the forward scattering light signal and the fluorescence signal can be obtained.

[0048] Please refer to Figure 3 and Figure 4 , Figure 3 is Figure 2 the flowchart of an embodiment before step S102 in Figure 4 is Figure 3 the cell scatter plot of an embodiment of steps S201-S202 in The steps included before step S102 are as follows:

[0049] S201: Obtain the first included angle a between the platelet region 14 in the three-dimensional cell scatter plot and the first direction X.

[0050] Optionally, please refer to Figure 4 (a), due to the area distribution characteristics of the platelet region 14, there is an included angle between the boundary line of the main distribution area of the platelet region 14 and the first direction X. In this embodiment, the first direction refers to the fluorescence signal. The first included angle a between the platelet region 14 and the fluorescence signal is calculated by using the Gaussian algorithm, which provides technical support for the subsequent rotation step.

[0051] S202: Determine the first angle b using the first included angle a, wherein the first included angle a and the first angle b are inversely related.

[0052] Optionally, please refer to Figure 4 (b), in order to reduce the overlap rate between the red blood cell region and the positive projection of the platelet region 14 in the first direction, so that it is lower than the set threshold, the rotation angle is dynamically adjusted according to the included angle between the platelet region 14 and the fluorescence signal, which is beneficial to the center value of the platelet region in the subsequent target histogram being closer to the 0 line, and the effect of reducing the overlap rate is better.

[0053] In the embodiment, the first included angle and the first angle are set to be 90°. In another embodiment, the first angle is directly set to a fixed value between 0° and 90°, and the rotation effect is best when the first angle is 45°. Of course, in other embodiments, the sum of the first included angle and the first angle can also be set to other angles, which are not limited here.

[0054] According to the above embodiment, the rotation angle is dynamically adjusted according to the included angle between the platelet region 14 and the fluorescence signal, which is beneficial to the center value of the platelet region in the target histogram being closer to the 0 line, and the overlapping rate is reduced, and the effect is better.

[0055] In the embodiment, before the step S201, the three-dimensional cell scatter plot is also rotated counterclockwise around the second direction by a second angle, so that at least part of the side scattering light signal is superimposed on the forward scattering light signal. Through the above-mentioned manner, the forward scattering light data in the three-dimensional cell scatter plot is unchanged, and the side scattering light signal representing the cell content is superimposed on the forward scattering light signal, which is beneficial to improving the recognition accuracy.

[0056] In a specific implementation scenario, the second angle is set to a fixed value between 0° and 90°, and the rotation effect is better when the second angle is 45°.

[0057] S103: Perform transmission processing on the two-dimensional cell scatter plot with the first coordinate axis to obtain a target histogram.

[0058] Optionally, the transmission processing refers to projection processing on the two-dimensional cell scatter plot, which is projected onto the first coordinate axis to generate the target histogram. The target histogram is generated based on the comprehensive light signal of the red blood cells in the aggregation region, wherein the horizontal coordinate of the target histogram is the comprehensive light signal, and the vertical coordinate is the cell quantity. For example, if the aggregation region includes 500 scatter points, and there are 200 points with a comprehensive light signal intensity equal to D, then on the target histogram, the vertical coordinate value of the point with the horizontal coordinate D is 200.

[0059] S104: Determine a red blood cell fragment region in the target histogram, and obtain a red blood cell fragment particle number from the red blood cell fragment region.

[0060] Through the above-mentioned rotation processing of the cell scatter plot, the light signals of multiple angles are integrated in the process of identifying the red blood cell fragments, which solves the problem of a large amount of overlap in each cell distribution region in the prior art, effectively reduces the misidentification probability of the red blood cell fragments, improves the recognition accuracy, and further reduces the probability of false positive of the blood test result.

[0061] Please refer to Figure 5 , Figure 5 is Figure 2Fig. 2 is a flowchart of an embodiment of step S104. Step S104 includes:

[0062] S301: Obtain peak information of the red blood cell region and the platelet region in the target histogram.

[0063] Optionally, refer to Figure 6 , Figure 6 is Figure 2 Fig. 3 is a flowchart of an embodiment of step S104. After step S302, the method includes:

[0064] S302: Determine the first boundary line of the red blood cell fragment region by using the peak information of the red blood cell region, and determine the second boundary line of the red blood cell fragment region by using the peak information of the platelet region.

[0065] Optionally, in the embodiment, the two side boundary lines of the red blood cell fragment region can be determined according to the peak information of the left and right regions. For example, the integrated light signal intensity corresponding to the peak value of the mature red blood cell region is P, and the left side boundary value T of the red blood cell fragment region is a*exp(b*P), wherein a and b are constant values set. According to the above embodiment, the red blood cell fragment region is dynamically divided according to the peak information of the red blood cell region and the platelet region, which is beneficial to improve the accuracy of region division and further improve the recognition effect.

[0066] In another embodiment, the first boundary line and the second boundary line of the red blood cell fragment region can be set as fixed values, as long as they are between the integrated light signal intensities corresponding to the peak values of the red blood cell region and the platelet region.

[0067] Of course, in other embodiments, the two side boundary lines of the cell fragment region can also be obtained according to other operation methods, such as logarithmic function, which is not limited here.

[0068] Optionally, refer to Figure 7 , Figure 7 is Figure 5 Fig. 4 is a flowchart of an embodiment of step S302. After step S302, the method includes:

[0069] S401: Obtain the red blood cell particle number of the red blood cell region in the target histogram.

[0070] Specifically, the technical method of obtaining the red blood cell particle number from the target histogram is the same as the method of obtaining the red blood cell fragment particle number, which is obtained by using the statistical method known in the prior art, and the specific statistical principle is not described here.

[0071] S402: Take the ratio of the number of red blood cell fragment particles to the number of red blood cell particles as a red blood cell fragment particle proportion value.

[0072] In the above manner, the final obtained proportion value can be used as a reference for doctor's diagnosis. The proportion of red blood cell fragments in the peripheral blood of a normal person should be less than 1%.

[0073] Please refer to Figure 8 , Figure 8 is a schematic diagram of an embodiment of the cell fragment recognition device of the present application. The recognition device includes an acquisition module 20, a rotation module 22, a transmission module 24 and a counting module 26. Specifically, the acquisition module 20 is configured to acquire a three-dimensional cell scatter plot constituted by the forward scattering light signal, the side scattering light signal and the fluorescence signal of the cell particles in the blood sample. The rotation module 22 is configured to obtain a two-dimensional cell scatter plot constituted by the forward scattering light signal and the fluorescence signal according to the three-dimensional cell scatter plot and a rotation process, wherein the overlap rate between the positive projections of the red blood cell region and the platelet region in the two-dimensional cell scatter plot on the first coordinate axis is lower than a threshold. The transmission module 24 is configured to perform a transmission process on the two-dimensional cell scatter plot with the first coordinate axis to obtain a target histogram. The counting module 26 is configured to determine a red blood cell fragment region in the target histogram and obtain the number of red blood cell fragment particles from the red blood cell fragment region. Through the above rotation process of the cell scatter plot, the light signals of multiple angles are integrated in the process of recognizing the red blood cell fragments, solving the problem of a large amount of overlap between the cell distribution regions in the prior art, effectively reducing the misrecognition probability of the red blood cell fragments, improving the recognition accuracy, and further reducing the probability of false positive of the blood test results.

[0074] Please refer to Figure 9 , Figure 9 is a structural schematic diagram of an embodiment of the red blood cell fragment recognition device of the present application. The device 30 includes a memory 300 and a processor 302 coupled with each other. The memory 300 stores program instructions. The processor 302 is configured to execute the program instructions to implement the quality evaluation method of the face image mentioned in any of the above embodiments.

[0075] Specifically, the processor 302 can also be referred to as a CPU (Central Processing Unit). The processor 302 can be an integrated circuit chip having a processing capability of signals. The processor 302 can also be a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor or the like. In addition, the processor 302 can be implemented by a plurality of integrated circuit chips jointly.

[0076] Please refer to Figure 10 , Figure 10 is a schematic diagram of a framework of an embodiment of the computer-readable storage medium of the present application. The computer-readable storage medium 40 stores a computer program 400, which can be read by a computer, and the computer program 400 can be executed by a processor to implement the quality evaluation method mentioned in any of the above embodiments. The computer program 400 can be stored in the computer-readable storage medium 40 in the form of a software product, including a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the method described in the various embodiments of the present application. The computer-readable storage medium 40 with storage function can be a U disk, a mobile hard disk, a ROM (Read-Only Memory), a RAM (Random Access Memory), a magnetic disk or an optical disk, etc. Various media that can store program codes, or a terminal device such as a computer, a server, a mobile phone, a tablet, etc.

[0077] The above is only an embodiment of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation, or direct or indirect application in other related technical fields, is also included in the patent protection scope of the present application.

Claims

1. A method for identifying red blood cell fragments, characterized in that: include: Obtaining a three-dimensional cell scattergram composed of forward scattered light signals, side scattered light signals and fluorescence signals of cell particles in a blood sample; obtaining a two-dimensional cell scattergram consisting of a forward scattered light signal and a fluorescence signal according to the three-dimensional cell scattergram and the rotation processing, wherein a first coordinate axis of the two-dimensional cell scattergram is the integrated light signal, and an overlap rate between orthographic projections of a red blood cell region and a platelet region in the two-dimensional cell scattergram on the first coordinate axis is lower than a threshold; Performing transmission processing on the two-dimensional cell scattergram using the first coordinate axis to obtain a target histogram; wherein the transmission processing is performing projection processing on the two-dimensional cell scattergram, projecting the two-dimensional cell scattergram onto the first coordinate axis to generate the target histogram; determining a red blood cell fragment region in the target histogram, and obtaining a number of red blood cell fragment particles from the red blood cell fragment region; The step of obtaining a two-dimensional cell scattergram consisting of forward scattered light signals and fluorescence signals according to the three-dimensional cell scattergram and rotation processing includes: Rotating the three-dimensional cell scattergram, and obtaining the two-dimensional cell scattergram according to the rotated three-dimensional cell scattergram; or, Obtaining a two-dimensional initial cell scattergram composed of forward scattered light signals and fluorescence signals before rotation according to the three-dimensional cell scattergram; rotating the two-dimensional initial cell scattergram to obtain the two-dimensional cell scattergram; Wherein, the first direction of the three-dimensional cell scattergram represents the fluorescence signal in the blood sample, the second direction represents the forward scattered light signal in the blood sample, and the third direction represents the side scattered light signal in the blood sample; The step of rotating the three-dimensional cell scattergram includes: rotating the three-dimensional cell scattergram counterclockwise around the third direction by a first angle; or The step of rotating the two-dimensional initial cell scatter plot to obtain the two-dimensional cell scatter plot comprises: The two-dimensional initial cell scattergram is rotated counterclockwise around the third direction by the first angle.

2. The identification method according to claim 1, characterized in that Before the step of rotating the three-dimensional cell scattergram counterclockwise around the third direction by a first angle or before the step of rotating the two-dimensional initial cell scattergram counterclockwise around the third direction by the first angle, the method includes: Obtaining a first angle between the platelet region and the first direction in the three-dimensional cell scattergram; The first angle is determined using the first included angle, wherein the first included angle is inversely correlated with the first angle.

3. The identification method according to claim 2, characterized in that The sum of the first included angle and the first angle is 90°.

4. The identification method according to claim 2, characterized in that Before the step of obtaining the first angle between the platelet region and the first direction in the three-dimensional cell scattergram, the method further includes: The three-dimensional cell scattergram is rotated counterclockwise around the second direction by a second angle, so that at least a portion of the side scattered light signal is superimposed on the forward scattered light signal.

5. The identification method according to claim 4, characterized in that: The second angle is between 0 degrees and 90 degrees.

6. The identification method according to claim 1, characterized in that The step of determining the red blood cell fragment area in the target histogram comprises: Acquiring peak information of the red blood cell region and the platelet region in the target histogram; A first boundary line of the red blood cell fragment area is determined using the peak information of the red blood cell area, and a second boundary line of the red blood cell fragment area is determined using the peak information of the platelet area.

7. The identification method according to claim 1, characterized in that: After the step of obtaining the number of red blood cell fragment particles from the red blood cell fragment area, the method further comprises: Obtaining the number of red blood cell particles in the red blood cell area in the target histogram; The ratio of the number of red blood cell fragment particles to the number of red blood cell particles is taken as the red blood cell fragment particle ratio value.

8. A device for identifying red blood cell fragments, characterized in that: The method comprises a memory and a processor coupled to each other, wherein the memory stores program instructions, and the program instructions are used to be executed by the processor to implement the method for identifying red blood cell fragments according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and the computer program is used to implement the method for identifying red blood cell fragments according to any one of claims 1 to 7.

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