WO2020133285A1 - 一种血液细胞参数修正方法、血液样本检测仪和存储介质 - Google Patents

一种血液细胞参数修正方法、血液样本检测仪和存储介质 Download PDF

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WO2020133285A1
WO2020133285A1 PCT/CN2018/125095 CN2018125095W WO2020133285A1 WO 2020133285 A1 WO2020133285 A1 WO 2020133285A1 CN 2018125095 W CN2018125095 W CN 2018125095W WO 2020133285 A1 WO2020133285 A1 WO 2020133285A1
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Prior art keywords
particles
information
pulse width
particle distribution
distribution information
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PCT/CN2018/125095
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English (en)
French (fr)
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叶波
王官振
李进
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深圳迈瑞生物医疗电子股份有限公司
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Priority to CN201880100554.5A priority Critical patent/CN113227757B/zh
Priority to PCT/CN2018/125095 priority patent/WO2020133285A1/zh
Publication of WO2020133285A1 publication Critical patent/WO2020133285A1/zh
Priority to US17/356,332 priority patent/US20210318222A1/en

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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
    • G01N15/10—Investigating individual particles
    • G01N15/14—Optical investigation techniques, e.g. flow cytometry
    • G01N15/1456—Optical investigation techniques, e.g. flow cytometry without spatial resolution of the texture or inner structure of the particle, e.g. processing of pulse signals
    • G01N15/1459—Optical investigation techniques, e.g. flow cytometry without spatial resolution of the texture or inner structure of the particle, e.g. processing of pulse signals the analysis being performed on a sample stream
    • 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
    • G01N15/02—Investigating particle size or size distribution
    • G01N15/0205—Investigating particle size or size distribution by optical means
    • 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
    • G01N15/14—Optical investigation techniques, e.g. flow cytometry
    • G01N15/1429—Signal processing
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/47—Scattering, i.e. diffuse reflection
    • G01N21/49—Scattering, i.e. diffuse reflection within a body or fluid
    • G01N21/53—Scattering, i.e. diffuse reflection within a body or fluid within a flowing fluid, e.g. smoke
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
    • G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
    • G01N21/64—Fluorescence; Phosphorescence
    • 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
    • G01N15/01—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials specially adapted for biological cells, e.g. blood cells
    • 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
    • G01N15/01—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials specially adapted for biological cells, e.g. blood cells
    • G01N2015/012—Red blood cells
    • 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
    • G01N15/01—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials specially adapted for biological cells, e.g. blood cells
    • G01N2015/012—Red blood cells
    • G01N2015/014—Reticulocytes
    • 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
    • G01N15/01—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials specially adapted for biological cells, e.g. blood cells
    • G01N2015/016—White blood cells
    • 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
    • G01N15/01—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials specially adapted for biological cells, e.g. blood cells
    • G01N2015/018—Platelets
    • 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
    • G01N2015/03—Electro-optical investigation of a plurality of particles, the analyser being characterised by the optical arrangement
    • 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
    • G01N15/14—Optical investigation techniques, e.g. flow cytometry
    • G01N2015/1402—Data analysis by thresholding or gating operations performed on the acquired signals or stored data
    • 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
    • G01N15/14—Optical investigation techniques, e.g. flow cytometry
    • G01N2015/1486—Counting 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
    • G01N15/14—Optical investigation techniques, e.g. flow cytometry
    • G01N2015/1493—Particle size

Definitions

  • the invention relates to the technical field of medical detection, in particular to a blood cell parameter correction method, a blood sample detector and a storage medium.
  • routine blood testing has become a routine medical method that is referred to when diagnosing diseases.
  • Routine blood testing is usually implemented using a medical particle analyzer such as a blood cell analyzer.
  • a medical particle analyzer such as a blood cell analyzer.
  • white blood cells White Blood Cells, WBC
  • red blood cells platelets
  • nucleated red blood cells reticulocytes and other cells
  • reticulocytes and other cells
  • particle aggregation or particle overlap may occur, for example, both red blood cell particles and white blood cell particles may occur.
  • white blood cell particles For example, when counting the number of white blood cells, during the collection and preparation of blood samples, the phenomenon of WBC particle aggregation and the overlap of WBC particles will occur, resulting in a low value of the WBC number obtained from the statistics, affecting the judgment of clinicians. Under normal circumstances, WBC particles are evenly distributed in the blood. However, during the collection or preparation of blood samples, WBC may be clustered together.
  • the overlapping of WBC particles refers to more One WBC particle is followed by one passing through the measurement hole. Based on the pulse width signal generated by the multiple WBC particles, the detection device causes the detection device to recognize the multiple WBC particles as a larger volume WBC particle.
  • the phenomenon of particle aggregation and particle overlap will result in inaccurate cell particle counting.
  • the phenomenon of WBC particle aggregation and WBC particle overlap will lead to inaccurate WBC particle counting, which will affect the judgment of clinicians.
  • the embodiments of the present invention are expected to provide a blood cell parameter correction method, a blood sample detector, and a storage medium to solve the problem of inaccurate number of blood cells counted when counting blood cells in the related art.
  • a blood cell parameter correction method includes:
  • the optical signal information includes forward scattered light information.
  • the light signal information includes side scattered light information and/or fluorescence signal information.
  • the correction rule includes:
  • the correction rule includes:
  • At least two pulse width interval ranges are set, and each of the pulse width interval ranges corresponds to a corresponding correction coefficient; wherein, the correction coefficient is positively related to the pulse width information;
  • Each of the correction coefficients is used to correct the corresponding number of particles in each of the pulse width interval ranges.
  • the correction rule includes:
  • the correction rule includes:
  • the optical signal information includes fluorescent signal information
  • the modifying the particle distribution information according to a preset modification rule includes:
  • the modifying the particle distribution information according to a preset modification rule includes:
  • the preset deletion rule includes:
  • the number of particles to be cut is determined based on the pulse width information to obtain particle distribution information after the number of particles is cut.
  • the reduced number of particles is inversely related to the pulse width information.
  • Optional also includes:
  • Optional also includes:
  • the method further includes:
  • Optional also includes:
  • the number of particles is determined and/or output according to the corrected particle distribution information.
  • the method further includes:
  • Bleeding shadow particles are identified and removed from the obtained particle light signal information, and then WBC particles are obtained.
  • a blood sample detector including:
  • At least one reaction cell used to provide a reaction place for blood samples and reagents
  • the optical detection device is used to irradiate the blood sample processed by the reagent with light, collect the optical signal generated by the light irradiation of each particle in the blood sample processed by the reagent, and convert it into an electrical signal to output the optical signal information;
  • a delivery device configured to deliver the blood sample processed by the reagent in the reaction cell to the optical detection device
  • the optical signal information includes forward scattered light information.
  • the light signal information includes side scattered light information and/or fluorescence signal information.
  • the correction rule stored in the processor includes:
  • the processor is used for:
  • At least two pulse width interval ranges are set, and each of the pulse width interval ranges corresponds to a corresponding correction coefficient; wherein, the correction coefficient is positively related to the pulse width information;
  • Each of the correction coefficients is used to correct the corresponding number of particles in each of the pulse width interval ranges.
  • the correction rule stored in the processor includes:
  • the correction rule stored in the processor includes:
  • the processor is used for:
  • the processor is used for:
  • the preset deletion rule stored in the processor includes:
  • the number of particles to be cut is determined based on the pulse width information to obtain particle distribution information after the number of particles is cut.
  • the reduced number of particles is inversely related to the pulse width information.
  • the processor is also used to:
  • the processor is also used to:
  • the processor is further configured to:
  • the processor is also used to:
  • the number of particles is determined and/or output according to the corrected particle distribution information.
  • the processor is used for: identifying and removing bleeding shadow particles from the obtained particle light signal information, and then obtaining WBC particles.
  • a computer-readable storage medium having stored thereon a correction program for blood cell parameters, the correction program for blood cell parameters being executed by a processor to implement any of the blood cell parameters described above The steps of the correction method.
  • the blood cell parameter correction method, blood sample detector and computer readable storage medium provided by the embodiments of the present invention acquire the light signal information of particles in the blood sample, and divide the blood sample according to the pulse width information in the light signal information Particles, the particle distribution information is obtained, and finally the particle distribution information is corrected according to a preset correction rule to obtain the corrected particle distribution information.
  • the particle distribution information in the blood sample is corrected by preset correction rules, which solves the problem of inaccurate number of blood cells counted in the related art when counting blood cells, and improves the accuracy of counting blood cells,
  • the operation process of blood cell number statistics is simplified, and the degree of intelligence of blood cell number detection equipment is improved.
  • FIG. 1 is a schematic flowchart of a blood cell parameter correction method according to an embodiment of the present invention
  • FIG. 2 is a schematic flowchart of another blood cell parameter correction method according to an embodiment of the present invention.
  • FIG. 3 is a schematic structural diagram of an optical flow chamber provided by an embodiment of the present invention.
  • FIG. 4 is a schematic diagram of a pulse width provided by an embodiment of the present invention.
  • FIG. 5 is a schematic diagram of a pulse area provided by an embodiment of the present invention.
  • FIG. 6 is a schematic diagram of an application scenario provided by an embodiment of the present invention.
  • FIG. 7 is a schematic diagram of another application scenario provided by an embodiment of the present invention.
  • FIG. 8 is a schematic flowchart of another blood cell parameter correction method according to an embodiment of the present invention.
  • FIG. 9 is a schematic diagram of another application scenario provided by an embodiment of the present invention.
  • FIG. 10 is a schematic diagram of still another application scenario provided by an embodiment of the present invention.
  • FIG. 11 is a schematic flowchart of another blood cell parameter correction method according to an embodiment of the present invention.
  • FIG. 12 is a schematic flowchart of a blood cell parameter correction method according to another embodiment of the present invention.
  • FIG. 13 is a schematic diagram of an application scenario provided by another embodiment of the present invention.
  • FIG. 14 is a schematic diagram of an application scenario provided by another embodiment of the present invention.
  • 15 is a schematic flowchart of another blood cell parameter correction method according to another embodiment of the present invention.
  • 16 is a schematic diagram of another application scenario provided by another embodiment of the present invention.
  • FIG. 17 is a schematic flowchart of another blood cell parameter correction method according to another embodiment of the present invention.
  • FIG. 18 is a schematic structural diagram of a blood sample detector provided by an embodiment of the present invention.
  • the terms "include”, “include” or any other variants thereof are intended to cover non-exclusive inclusion, so that a method or device including a series of elements includes not only the explicitly recorded Elements, and also include other elements not explicitly listed, or include elements inherent to the implementation of the method or device. If there are no more restrictions, the element defined by the sentence “include a" does not exclude that there are other relevant elements in the method or device including the element (such as the steps in the method or the unit in the device) , The unit here may be part of the circuit, part of the processor, part of the program or software, etc.).
  • first ⁇ second ⁇ third involved in the embodiment of the present invention is only to distinguish similar objects, and does not represent a specific order for objects. Understandably, “first ⁇ second ⁇ third” “Three” can be exchanged in a specific order or sequential order when allowed. It should be understood that the objects distinguished by “first ⁇ second ⁇ third” may be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein.
  • An embodiment of the present invention provides a blood cell parameter correction method. Referring to FIG. 1, the method includes the following steps:
  • Step 101 Obtain light signal information of particles in a blood sample.
  • the light signal information may include forward scattered light information, and/or side scattered light information, and/or fluorescent signal information. That is, the light signal information may include only one of forward scattered light information, side scattered light information, and fluorescent signal information, or any combination thereof.
  • step 101 "obtaining light signal information of particles in a blood sample” may be implemented by a blood sample detector.
  • the particles in the blood sample may refer to all types of cell particles in the blood sample, and may include, for example, WBC, red blood cells, platelets, nucleated red blood cells, reticulocytes, and other cell particles in the blood sample.
  • the optical signal information may include characteristic information of the optical signal for distinguishing and identifying the blood sample particles. For example, after the blood sample particles are processed by the optical signal, the pulse width of the optical signal corresponding to the blood sample particles or the pulse peak value of the optical signal are detected.
  • the light signal can include forward scattered light (Forward Scatter (FSC), side Three light signals: Side Scatter (SSC) and Fluorescence (FL).
  • FSC forward scattered light
  • SSC Side Scatter
  • FL Fluorescence
  • FSC can be used to detect the size of the particles
  • SSC can detect the complexity of the internal structure of the particles
  • FL can detect the deoxyribonucleic acid in the particles.
  • Deoxyribonucleic Acid, DNA and ribonucleic acid (Ribonucleic Acid, RNA) and other substances that can be dyed with fluorescent dyes.
  • Optical signal information such as pulse width information of the corresponding optical signal.
  • the particle size, internal structure, and content of substances that can be dyed with fluorescent dyes are different between different types of particles, so different types of particles can be distinguished by reflecting the light signal information of the particles, for example, from particles Red blood cells, white blood cells, platelets and so on.
  • white blood cells white blood cells can also be subdivided into five types of cells: neutrophils, lymphocytes, eosinophils, basophils and monocytes. Therefore, different types of particles can be distinguished by optical signal information.
  • the pulse width information of the light signal corresponding to the particles of different sizes in the blood sample is different, the particles of different sizes in the blood sample can be distinguished according to the pulse width information in the light signal information, and the number of particles of various sizes in the blood sample can be counted. Therefore, for a certain type of cells, the pulse width information of the optical signal can be used to distinguish cells of different sizes, thereby facilitating the counting of the number of cells, such as the number of WBC cells.
  • Step 102 Divide the particles according to the pulse width information in the optical signal information to obtain particle distribution information.
  • step 102 divide particles according to the pulse width information in the light signal information to obtain particle distribution information
  • the blood sample detector divides the particles in the blood sample according to the pulse width information in the obtained optical signal information, determines the particles in the blood sample, and obtains the distribution information of the particles in the blood sample. For example, after recognizing a certain type of particle, the particle of this type is divided according to the pulse width information to obtain the particle distribution information of this type of particle, such as the distribution information of WBC particles with pulse width and the distribution of red blood cell particles with pulse width Information, distribution information of platelet particles with pulse width, distribution information of nucleated red blood cell particles with pulse width, and distribution information of reticulocyte particles with pulse width.
  • the distribution information of WBC particles with pulse width is mainly taken as an example for description.
  • the blood shadow particles can be identified and removed from the acquired particle light signal information, and then the WBC particles are obtained. Then divide the WBC particles according to the pulse width information in the optical signal information to obtain the WBC particle distribution information. Bleeding shadow particles can be identified from the FSC/SSC/FL three-dimensional signals in the acquired particle light signal information, and bleeding shadow particles can also be identified from the pulse width information in the acquired particle light signal information, which is not specifically limited herein.
  • Step 103 Correct the particle distribution information according to a preset correction rule to obtain the corrected particle distribution information.
  • the correction rule is related to the pulse width information in the optical signal information.
  • step 103 "correcting the particle distribution information according to a preset correction rule to obtain corrected particle distribution information" may be implemented by a blood sample detector.
  • the preset correction rules are determined according to the characteristics of particle overlap and/or particle aggregation. In this way, the preset correction rules are used to modify the particle distribution information to correct the number of particles and solve the problems caused by particle overlap and/or particle aggregation. When the number of particles is low, the number of particles in the blood sample finally corrected is more consistent with the actual number.
  • the blood cell parameter correction method obtained by the embodiment of the present invention obtains the light signal information of the particles in the blood sample, and divides the particles in the blood sample according to the pulse width information in the light signal information to obtain the particle distribution information.
  • the set correction rule corrects the particle distribution information to obtain the corrected particle distribution information.
  • the particle distribution information in the blood sample is corrected through preset correction rules, which solves the problem of inaccurate number of blood cells counted in the related art when counting blood cells (such as white blood cells), and improves the count of blood cells
  • the accuracy of the method simplifies the operation process of blood cell number statistics and improves the degree of intelligence of blood cell number detection equipment.
  • the blood sample detector may also choose to perform step A or step B or step C or step D:
  • Step A Output the corrected particle distribution information.
  • the corrected particle distribution information can be passed through the display of the blood sample detector
  • the output is displayed.
  • the modified particle distribution information can be displayed on the display of the blood sample detector by using a scatter diagram, a data array, a scatter diagram combined with a data array, and the like.
  • Step B Output the particle distribution information before and after correction.
  • the particle distribution information before correction can be the particles obtained in step 102
  • the distribution information and the corrected particle distribution information that is, the corrected particle distribution information obtained in step 103, are displayed on the display of the blood sample detector.
  • the particle distribution information before correction and the particle distribution information after correction can be displayed on the display of the blood sample detector by using a scatter diagram, a data array, a scatter diagram combined with a data array, and the like.
  • Step C issue a prompt that the particle distribution information has been corrected; and/or issue a prompt and/or alarm for particle aggregation according to the correction range.
  • particles that prompt the user using the blood sample detector to generate the blood sample can be generated Prompt information where the distribution information has been corrected, for example, "WBC particle information has been corrected".
  • the prompt information can be directly displayed on the display of the blood sample detector, or the blood sample detector can also send the prompt information to the mobile terminal device that has a communication connection with the blood sample detector.
  • the prompt and/or alarm of particle aggregation can be issued according to the correction range, or the prompt and/or alarm of particle aggregation degree can be issued according to the correction range, for example, the prompt information such as “particle aggregation” and “particle aggregation degree is too high” or A visual alarm sounds on the display.
  • the degree of particle aggregation can be judged according to the correction range. The higher the correction range, the higher the degree of aggregation.
  • the correction range can be judged according to the relationship between the number of particles before correction and the number of particles after correction, for example, according to the proportional relationship or difference relationship between the two.
  • Step D Determine and/or output the number of particles according to the corrected particle distribution information.
  • the blood sample detector corrects the particle distribution information of the blood sample according to the preset correction rule to obtain the corrected particle distribution information, and then counts the number of particles in the corrected particle distribution information to obtain
  • the actual number of particles in the blood sample is the number of particles.
  • the number of particles may be displayed on the display of the blood sample detector.
  • an embodiment of the present invention provides a blood cell parameter correction method, which is applied to a blood sample detector.
  • the method includes the following steps:
  • Step 201 Obtain light signal information of particles in a blood sample.
  • the light signal information may include forward scattered light information, and/or side scattered light information, and/or fluorescent signal information. That is, the light signal information may include only one of forward scattered light information, side scattered light information, and fluorescent signal information, or any combination thereof.
  • the optical signal information includes FSC information as an example for description.
  • the size of the particles in the blood sample can be expressed by the time t when the particles pass through the measuring hole of the optical flow cell in the blood sample detector, as shown in FIG. 3, the length of the optical flow cell G is L, assuming to be detected
  • the blood sample detector can measure the size of the particles in the blood sample by recording the time when the particles in the blood sample pass through the optical flow chamber, specifically: when the particles in the blood sample pass through the measurement hole of the optical flow chamber , The blood sample detector is excited to send a pulse signal until the particles in the blood sample completely pass through the optical flow chamber, the resulting pulse signal can be shown in Figure 4, where: the abscissa is the time t of the particles passing through the optical flow chamber, the unit is Milliseconds (ms), the ordinate is the pulse intensity; A is the pulse peak value, which is the pulse intensity value from the baseline to the pulse maximum; B is the pulse width (referred to as the pulse width), which can be used to indicate the passage of particles in the blood sample The actual time of the measuring hole in the optical flow cell.
  • the pulse width may be the time width between two intersection points of the straight line indicated by the pulse intensity curve and the preset pulse intensity threshold.
  • the pulse peak value A is about 800
  • the corresponding pulse width B is about 25 ms.
  • the diameter of the particles in the detected blood sample will be larger than that of a normal WBC particle
  • the larger the diameter the longer the time to pass through the measurement hole of the optical flow chamber, and the corresponding pulse width becomes larger.
  • the pulse width information of the particles in the blood sample may be the forward scattered light pulse width (Forward Scattered light pulse width, FSCW), or may be the side scattered light pulse width (Side Scatter light edge pulse) Width, SSCW), or Fluorescence Pulse Width (FLW).
  • FSCW Forward Scattered light pulse width
  • SSCW Side Scatter light edge pulse
  • FLW Fluorescence Pulse Width
  • the pulse width can also be replaced by the area of the pulse, which can be the pulse area of any one of the three types of light of FSC, SSC, and FL, where the pulse area can be specifically shown as C in FIG. 5 Is the area enclosed by the pulse intensity curve between the abscissa t1 corresponding to the first intersection of the pulse intensity curve and the pulse intensity threshold and the abscissa t2 corresponding to the last intersection.
  • Step 202 Divide the particles in the blood sample according to the pulse width information in the optical signal information to obtain particle distribution information.
  • the particles in the blood sample can be divided according to the pulse width information in different light signal information to obtain the particle distribution information corresponding to each type of particles, for example
  • the obtained distribution information of WBC particles is shown in FIG. 6, wherein the abscissa in FIG. 6 represents the pulse width, and the ordinate represents the pulse peak value of the forward scattered light.
  • Each black dot in the figure represents a WBC particle.
  • Step 203 Acquire at least two preset pulse width interval ranges.
  • the at least two preset pulse width interval ranges may be empirical theoretical values obtained based on a large number of experimental analyses, which can be continuously corrected in the actual application process.
  • Step 204 Correct the particle distribution information according to the pulse width interval to obtain the corrected particle distribution information.
  • the correction rule is related to the pulse width information in the optical signal information.
  • the obtained particle distribution information is divided according to the set at least two pulse width interval ranges, the particles are divided into particles in at least two regions, and the number of particles in different regions is counted, and then according to the setting
  • the correction coefficients corresponding to the at least two pulse width interval ranges correct the number of particles in the corresponding area to obtain corrected particle distribution information.
  • the preset pulse width interval range in the correction rule stored in the blood sample detector may be two, which are a haploid pulse width range and a polyploid pulse width range, that is, according to the haploid pulse width range and
  • the range of the polyploid pulse width divides the particle distribution information into a haploid particle distribution area and a polyploid particle distribution area, so that the two particle distribution areas can be corrected by their respective methods, and the corrected Particle distribution information.
  • the preset pulse width range in the correction rule stored in the blood sample detector may also be more than two, for example, six, which are respectively the range of the haploid pulse width, the diploid pulse width, and the triploid pulse width.
  • Range, tetraploid pulse width range, pentaploid pulse width range and hexaploid pulse width range that is, the particle distribution information is divided into haploid particle distribution area and diploid according to the six preset pulse width ranges Particle distribution area, triploid particle distribution area, tetraploid particle distribution area, pentaploid particle distribution area and hexaploid particle distribution area, so that these two particle distribution areas can be corrected by their respective methods, The corrected particle distribution information can be obtained.
  • the haploid pulse width range refers to the pulse width measured when a single cell particle passes through the optical flow chamber, that is, the corresponding pulse width range when the particle diameter is one particle diameter (one times the particle diameter).
  • the corresponding pulse width range is the diploid pulse width range when the particle diameter is twice the particle diameter.
  • the triploid pulse width range is the pulse width corresponding to the triple particle diameter Range
  • the range of tetraploid pulse width is the range of pulse width corresponding to four times the particle diameter
  • the range of pentaploid pulse width is the range of pulse width corresponding to five times the particle diameter
  • the range of hexaploid pulse width is the pulse corresponding to six times the particle diameter Wide range, etc., and so on.
  • twice the particle diameter, three times the particle diameter, four times the particle diameter, five times the particle diameter and six times the particle diameter occur due to cell aggregation, usually 2 cell particles aggregate, 3 cells Particle aggregation, 4 cell particle aggregation, and 8 cell particle aggregation may have twice the particle diameter.
  • 2 cell particle aggregation, 3 cell particle aggregation, and 4 cell particle aggregation there are 2 cell particle aggregation, 3 cell particle aggregation, and 4 cell particle aggregation. Schematic diagram showing that twice the particle diameter appears when 8 cell particles are aggregated.
  • the above-mentioned haploid pulse width range, diploid pulse width range, ...hexaploid pulse width range, polyploid pulse width range can all be empirical values.
  • a blood cell parameter correction method provided in other embodiments of the present invention is applied to a blood sample detector.
  • step 204 may be specifically performed It is implemented by the following steps 204a-204b, where the correction rule is: setting at least two pulse width interval ranges, each of the pulse width interval ranges corresponding to a corresponding correction coefficient; wherein, the correction coefficient and the pulse width information are positive Correlation; use each of the correction coefficients to correct the corresponding number of particles in each of the pulse width interval ranges.
  • Step 204a Determine the correction coefficient corresponding to each pulse width interval range.
  • the correction coefficient is positively related to the pulse width.
  • the correction coefficient is positively related to the pulse width, that is, the correction coefficient changes according to the change of the pulse width.
  • the correction coefficient becomes larger as the range of the pulse width interval becomes larger.
  • the first pulse width interval range is (a, b), corresponding to one correction coefficient, such as the first correction coefficient;
  • the second pulse width interval range is (b, c), corresponding to another correction coefficient, such as the first Two correction coefficients;
  • the third pulse width interval range is (c, d), corresponding to another correction coefficient, for example, the third correction coefficient; where, a ⁇ b ⁇ c ⁇ d, correspondingly, the first correction coefficient is less than or Equal to the second correction coefficient, the second correction coefficient is less than or equal to the third correction coefficient.
  • the correction coefficient corresponding to each pulse width interval range is preset, which may be an empirical value or an empirical formula.
  • pulse width interval ranges when two or more pulse width interval ranges are set based on the WBC particle distribution information, for example, as shown in FIG. 9, there are six pulse width interval ranges, and the particle distribution information corresponding to each pulse width interval range is specifically: pulse width interval
  • the particle distribution information G1 in the range of 0-25 ms is the particle distribution information of the haploid region
  • the particle distribution information in the pulse width interval range of 25-33 ms H1 is the particle distribution information of the diploid region
  • the pulse width interval range is 33-41 ms.
  • the particle distribution information I1 is the particle distribution information of the triploid region
  • the particle distribution information within the pulse width interval range of 41-49ms J1 is the particle distribution information of the tetraploid region
  • the particle distribution information K1 of the pulse width interval range of 49-57ms is five
  • the particle distribution information of the ploidy region, the particle distribution information L1 within the pulse width interval range of 57-65 ms is the particle distribution information of the hexaploid region.
  • haploid refers to cell particles with a diameter of one cell particle. Due to the aggregation and overlapping of cells, there are diploid, triploid, tetraploid, pentaploid and hexaploid.
  • the correction coefficient set by the information is an empirical value, which is a constant, followed by 1, 3, 10, 20, 30, and 40.
  • the correction coefficient is positively related to the pulse width.
  • the pulse width interval range can be divided by using the equal pulse width division method as shown in FIG. 9; the unequal pulse width as shown in FIG. 10 can also be used The division method divides the pulse width interval range.
  • Step 204b Use each correction coefficient to correct the corresponding number of particles in each pulse width interval range.
  • the number of particles within each pulse width interval is counted, and then each correction coefficient is multiplied by the corresponding number of particles within each pulse width interval to achieve Correction of the number of particles.
  • a sample is collected, where the reference value of WBC is 6.72 ⁇ 10. ⁇ 9/L, and the count value given by the white blood cell channel after the test of the BC-6000 instrument produced by Shenzhen Mindray Biomedical Co., Ltd. is 3.72 ⁇ 10. ⁇ 9/L, the white blood cell channel contrast reference value is 45% lower.
  • Figure 6 shows an example of the fluorescence-forward scattering light dispersion of the WBC aggregate sample. Dot map. Counting the number of particles in different pulse width intervals shown in FIG.
  • the number of particles corresponding to the particle distribution information G2 in the diploid region is 2115, and the number of particles corresponding to the particle distribution information H2 in the diploid region is 215.
  • the number of particles corresponding to the particle distribution information I2 in the triploid region is 110, the number of particles corresponding to the particle distribution information J2 in the tetraploid region is 10, and the number of particles corresponding to the particle distribution information K2 in the triploid region is 5, six times
  • the number of particles corresponding to the particle distribution information L2 in the body region is 2; if the correction coefficients set for the six pulse width ranges in FIG. 10 are the same as the correction coefficients set in the six pulse width ranges in FIG.
  • the corresponding correction in step 204a is used
  • the particle distribution information in the area is accumulated, and the actual number of WBC particles in FIG. 6 is 4290, which corresponds to a WBC value of 6.73 ⁇ 10. ⁇ 9/L, which corresponds to the reference value of 6.
  • a blood cell parameter correction method provided by other embodiments of the present invention is applied to a blood sample detector.
  • step 205 may also be selected to implement :
  • Step 205 Correct the particle distribution information according to the preset function.
  • the preset function is an increasing function with the pulse width information as a variable, and the particle distribution information is modified accordingly according to the calculation result (dependent variable) of the function.
  • the preset function can be a function that takes pulse width information as a variable and correction coefficient as a dependent variable, that is, the function calculation result can be a correction coefficient that becomes larger according to the pulse width becoming larger, and then the particle distribution information is based on the correction coefficient.
  • the number of particles corresponding to the pulse width is corrected. For example, the correction coefficient is multiplied by the number of particles corresponding to the pulse width to obtain the number of particles corresponding to the corrected pulse width.
  • the preset function may also be a function that takes the pulse width information and the number of particles corresponding to the corresponding pulse width as variables, and the correction coefficient as the dependent variable.
  • the preset function is a preset function related to the pulse width information, and is an empirical formula.
  • steps 205a-205b may be specifically implemented:
  • Step 205a Determine the correction coefficient according to the preset function.
  • the preset function may be a piecewise function related to the pulse width information.
  • the corresponding preset function of the WBC particle distribution information is a preset constant, for example, 1; when the corresponding pulse width information is greater than 25 ms, it is related to the pulse width information. Default function.
  • the calculation process using the preset function when the corresponding pulse width information is greater than 25ms is steps a-b:
  • Step a Calculate the product of each pulse width information and the first preset coefficient separately to obtain the first value.
  • a represents the first preset coefficient, which is usually a constant and an empirical value. In different application scenarios, it can be changed according to the actual application scenario, or it can be continuously corrected.
  • a may be 0.925
  • w represents each pulse width information. That is to say, based on the preset function, the WBC particle distribution information in FIG. 6 can be divided into the particle distribution information as shown in FIG. 13, that is, the corresponding correction coefficient in the area of FIG. 13E (the pulse width information is less than or equal to 25ms) is A constant, generally set to 1, w j can be each pulse width of particles distributed in the area of Fig.
  • the value of j is a positive integer, assuming that the pulse width corresponding to the area of Fig. 13F According to statistics, there are n in total, and the value of j is 1, 2, ..., n.
  • Step b Calculate the sum of the first value and the second preset coefficient to obtain the corresponding correction coefficient.
  • b is the second preset coefficient, which is an empirical value, and can be changed according to the actual application scenario in different application scenarios, or can be continuously corrected.
  • the value of b may be -24.75
  • Step 205b Correct the particle distribution information according to the correction coefficient.
  • the correction coefficient is positively related to the pulse width information.
  • a sample is collected, where the reference value of WBC is 6.72 ⁇ 10. ⁇ 9/L, and the count value given by the white blood cell channel after the test of the BC-6000 instrument produced by Shenzhen Mindray Biomedical Co., Ltd. is 3.72 ⁇ 10. ⁇ 9/L, the white blood cell channel contrast reference value is 45% lower.
  • Figure 6 shows an example of the fluorescence-forward scattering light dispersion of the WBC aggregate sample. Dot map. Count and correct the number of particles in the range of haploid pulse width in FIG.
  • the actual number of particles is 2160. Therefore, the actual total number of particles is 4275, which corresponds to a WBC value of 6.71 ⁇ 10. ⁇ 9/L, which basically corresponds to the reference value of 6.72 ⁇ 10. ⁇ 9/L. Corrected correctly.
  • the process of setting the preset function may be: determining the average value of particle aggregation within each pulse width interval, and the specific formula for determining the average value of particle aggregation may be: Where i is the number of particle aggregations that occur when particles aggregate within each pulse width interval. For example, when the WBC particles aggregate at twice the particle diameter, it is assumed that from 2 WBC particles to 8 WBC particles aggregate cells with equal probability, the above formula can be used to calculate the number of WBC particles aggregated within the range of twice the body pulse width The average value of is 5, therefore, in the case of particle aggregation, when counting the actual number of WBC particles aggregated within the diploid pulse width, the number of WBC particles counted within the diploid pulse width can be multiplied by 5 times the coefficient.
  • the average number of WBC particles aggregated within the range of triploid pulse width is 15; the average number of WBC particles aggregated within the range of tetraploid pulse width is 25; The average number of aggregated WBC particles is 35, and the average number of aggregated WBC particles in the pulse width range of six times or more is 45. Because the phenomenon of WBC particle aggregation and WBC particle overlap will appear in the same area, it will interfere with the aggregation of WBC particles. For this reason, the number of aggregated particles corresponding to twice the body pulse width range and above can be appropriately reduced. Decrease the average value as the correction factor.
  • the average pulse width of the detected number of particles of haploid, diploid, triploid, tetraploid, pentaploid, and hexaploid is about 18, 30, 40, 50, 60, 70.
  • the fitted curve is roughly through the points (x, y) composed of pulse width-correction coefficients, where x is the pulse width value and y is the correction coefficient corresponding to each pulse width range, For example, the point of the diploid area is (30,5), and the point of the triploid area is (40,15).
  • the fitting can be in the form of straight-line fitting or quadratic curve.
  • a linearly fitting particle compensation curve is shown in Figure 14, where the pulse width has five control points in the interval of 27 to 70, which are (30,3), (40,10), (50,20) , (60,30), (70,40), a function corresponding to the correction line that generates a continuous aggregated particle compensation coefficient by straight-line fitting in this interval can be used to correct aggregated particles.
  • the blood cell parameter correction method obtained by the embodiment of the present invention obtains the light signal information of the particles in the blood sample, and divides the particles in the blood sample according to the pulse width information in the light signal information to obtain the particle distribution information.
  • the set correction rule corrects the particle distribution information to obtain the corrected particle distribution information.
  • the particle distribution information in the blood sample is corrected through preset correction rules, which solves the problem of inaccurate number of blood cells counted due to particle aggregation and overlap in the related art when counting blood cells, and improves the statistics
  • the accuracy of the blood cell number simplifies the operation process of blood cell number statistics, and improves the degree of intelligence of the blood cell number detection equipment.
  • an embodiment of the present invention provides a blood cell parameter correction method, which is applied to a blood sample detector.
  • the method includes the following steps:
  • Step 301 Obtain light signal information of particles in a blood sample.
  • the optical signal information includes fluorescent signal information.
  • the corresponding optical signal information includes FL signal information and FSC information, or includes FL signal information and SSC information, or includes FL signal information, FSC information, and SSC information, or includes FL signal information and other optical signals information.
  • the FL signal and the laser signal are used to stain the blood sample to obtain the distribution information of the particles in the blood sample with FL signal information and FSC information.
  • Step 302 Divide the particles in the blood sample according to the pulse width information in the optical signal information to obtain particle distribution information.
  • Step 303 Screen particles with a fluorescence signal value lower than a preset threshold to obtain particle distribution information after screening.
  • the present invention taking the case of twice the particle diameter as an example to illustrate the difference between particle aggregation and other cases (such as overlapping particles).
  • particle overlap usually only two particles overlap, and the probability of three or more particles overlapping is extremely low, so the corresponding FL signal strength generated is probably the sum of the FL signal strengths of the two particles.
  • particle aggregation occurs, not only the aggregation of two particles produces twice the particle diameter, 8 particles also produce twice the particle diameter, on average about 5 particles, the corresponding FL signal strength is also five times the average Particle FL intensity. Therefore, the FL intensity when particle aggregation occurs will be greater than the FL signal intensity due to particle overlap and other conditions.
  • the limit of the FL signal strength can rule out the interference of other conditions (such as particle overlap) on the actual particle distribution information collected when the particles are aggregated. Therefore, for the above-mentioned polyploid region, for example, the above-mentioned region with a pulse width greater than 25 ms, particles with a fluorescence signal value lower than a preset threshold can be screened out.
  • a haploid region such as the above-mentioned region with a pulse width of less than 25 ms, can also filter out particles with a fluorescence signal value below the preset threshold, but there are fewer particles with a fluorescence signal value below the preset threshold.
  • the particle distribution information after sieving can be obtained as shown in FIG. 16, where the abscissa is the pulse width , The unit time is ms, and the ordinate is forward scattered light.
  • the preset threshold is an empirical value. In different application scenarios, the corresponding preset threshold is different. For example, the preset threshold is 3500. Of course, this preset threshold may be a fixed value, or it may be different according to different samples, and can be set manually or after the machine judges.
  • Step 304 Modify the particle distribution information after sieving according to a preset modification rule.
  • a blood cell parameter correction method provided by the present invention may be that after a blood sample detector performs fluorescent processing and laser processing on a blood sample, the WBC particle distribution information in the blood sample is determined and sifted from the WBC particle distribution information
  • a sample is collected, the reference value of WBC is 6.72 ⁇ 10. ⁇ 9/L, and the count value given by the white blood cell channel after the test of the BC-6000 instrument produced by Shenzhen Mindray Biomedical Co., Ltd. is 3.72 ⁇ 10. ⁇ 9/L, the white blood cell channel is 45% lower than the reference value.
  • the microscopic examination confirmed that WBC aggregation occurred in the sample.
  • Figure 6 shows an example of the fluorescence-forward scattering light scattering point of the WBC aggregate sample.
  • the actual number of WBC particles is 2170; correspondingly, the actual number of WBC particles with a pulse width information less than or equal to 25ms is 2170 plus the actual number of WBC particles with a pulse width information greater than 25ms is 2115, that is The actual number of WBC particles in the blood sample is 4285, the corresponding WBC value is 6.73 ⁇ 10. ⁇ 9/L, which basically corresponds to the reference value of 6.72 ⁇ 10. ⁇ 9/L, and the correction is considered correct.
  • the screened particles can be considered as particles with overlapping particles. For the case of overlapping particles, the industry has corresponding calculation rules. These calculation rules can be taken into account when setting correction rules.
  • another blood cell parameter correction method provided by the present invention may be that after the blood sample detector performs fluorescence processing and laser processing on the blood sample, the WBC particle distribution information in the blood sample is determined, and from the WBC particle distribution information Sieve out the WBC particles carrying the FL signal whose signal value is lower than the preset threshold of 3500 to obtain the WBC particle distribution information after sieve; set at least two pulse width interval ranges, and carry out the WBC particle distribution signal according to the pulse width interval range
  • the specific process of correction is as follows: the preset pulse width interval ranges (0, 25), (25, 33), (33, 41), (41, 49), (49, 57) are used to sieve the WBC particles
  • the distribution information is divided into 6 regions of particle distribution information, and it is determined that the particle distribution information in the pulse width interval range of 0 to 25ms is the particle distribution information of the haploid region, and the particle distribution information in the pulse width interval range of 25 to 33ms is double Particle distribution information in the body region, the particle distribution information in the pulse
  • a sample is collected, the reference value of WBC is 6.72 ⁇ 10. ⁇ 9/L, and the count value given by the white blood cell channel after the test of the BC-6000 instrument produced by Shenzhen Mindray Biomedical Co., Ltd. is 3.72 ⁇ 10. ⁇ 9/L, the white blood cell channel is 45% lower than the reference value.
  • the microscopic examination confirmed that WBC aggregation occurred in the sample.
  • Figure 6 shows an example of the fluorescence-forward scattering light scattering point of the WBC aggregate sample.
  • the number of particles in the haploid area of the sample is 2115
  • the number of particles in the diploid area is 215
  • the number of particles in the triploid area is 110
  • the number of particles in the tetraploid area is 10
  • the number of particles in the pentaploid area is 5.
  • the number of particles in the polyploid area of hexaploid and above is 2.
  • the number of post-screening WBC particles corresponding to the particle distribution information of the diploid area is 176, the number of post-screening WBC particles corresponding to the particle distribution information of the triploid area is 80, and the particle distribution of the tetraploid area
  • the number of WBC particles after the sieve corresponding to the information is 5, the number of WBC particles after the sieve corresponding to the particle distribution information of the pentaploid area is 2, and the number of WBC particles after the sieve corresponding to the particle distribution information of the hexaploid area is 1; each pulse is calculated separately
  • the product of the number of WBC particles in the wide interval and the corresponding correction factor for each pulse width interval can be obtained as the actual number of WBC particles in the haploid region is 2115, the diploid region
  • the actual number of WBC particles after the sieve corresponding to the particle distribution information is 880, the actual number of WBC particles after the sieve corresponding to the particle distribution information of the triploid region is 1040, and the actual number of W
  • the actual number of WBC particles after sieve corresponding to the particle distribution information of the pentaploid region is 70, and the actual number of WBC particles after the sieve corresponding to the particle distribution information of the hexaploid region is 45; Finally, the actual number of WBC particles in the blood sample is each pulse
  • the cumulative sum of the actual number of WBC particles after sieve corresponding to a wide range is 4275, the corresponding WBC value is 6.71 ⁇ 10. ⁇ 9/L, which basically corresponds to the reference value of 6.72 ⁇ 10. ⁇ 9/L, and the correction is considered correct .
  • the preset correction rules are set in consideration of the number of particles reduced by sieve. This part of the particles is sifted, which will affect the final statistical number of particles, so this factor can be considered when setting the correction rules. Of course, since the influence is not large, in some embodiments, the influence of this part of sieve reduction particles can also be ignored.
  • the blood cell parameter correction method obtained by the embodiment of the present invention obtains the light signal information of the particles in the blood sample, and divides the particles in the blood sample according to the pulse width information in the light signal information to obtain the particle distribution information.
  • the set correction rule corrects the particle distribution information to obtain the corrected particle distribution information.
  • the particle distribution information in the blood sample is corrected by the preset correction rule, which solves the problem of inaccurate number of blood cells due to particle overlap when counting blood cells in the related art, and improves the number of blood cells
  • the accuracy of the method simplifies the operation process of blood cell number statistics and improves the degree of intelligence of blood cell number detection equipment.
  • the embodiment of the present invention provides a blood cell parameter correction method, which is applied to a blood sample detector, mainly for the case where there is aggregation and overlap of cell samples.
  • the method includes the following steps 401 to Step 403:
  • Step 401 Obtain light signal information of particles in a blood sample.
  • Step 402 Divide the particles in the blood sample according to the pulse width information in the optical signal information to obtain particle distribution information.
  • Step 403 Delete the number of particles according to a preset deletion rule to obtain particle distribution information after the reduced number of particles.
  • the preset pruning rule is determined according to the characteristic of overlapping particles. Taking the diameter of twice the volume of particles as an example to explain the reason why the number of particles needs to be deleted according to the preset deletion rule: when two particles overlap, the pulse width generated is about 1.5 times the pulse width generated by one particle. However, when particle aggregation occurs, particle aggregation of two to eight particles can produce twice the pulse width of the particles, and the corresponding pulse width is also 1.5 times the pulse width of one particle. Therefore, particle overlap and particle aggregation will be superimposed on the pulse width, so it is necessary to exclude the interference of particle overlap on particle statistics.
  • step 403 may be implemented by step 403a or step 403b:
  • Step 403a Determine the number of particles to be cut based on the blood sample size and pulse width information, and obtain the particle distribution information after the number of particles is cut.
  • the reduced number of particles is inversely related to the pulse width.
  • the number of truncated particles is inversely related to the pulse width, that is, the truncated particles change according to the change of the pulse width. For example, the number of truncated particles decreases as the range of the pulse width increases.
  • the first pulse width interval range is (a, b), corresponding to a set number of particles to be deleted, for example, the first reduced particle number;
  • the second pulse width interval The range is (b, c), corresponding to another set of the number of particles to be cut, for example, the number of second cut particles;
  • the third pulse width interval range is (c, d), corresponding to another setting
  • the number of particles that need to be pruned is, for example, the number of the third pruned particle; where, a ⁇ b ⁇ c ⁇ d, correspondingly, the first pruned particle is greater than or equal to the number of the second pruned particle, the second pruned The number of particles is greater than or equal to the number of third cut particles.
  • the blood sample size refers to the amount of blood sample collected for testing. For example, if a 35 microliter (uL) blood sample is collected, the 35uL blood sample is analyzed, and the 35uL blood sample should be deleted based on the pulse width information. For the number of particles, if an 80uL blood sample is collected, the 80uL blood sample is analyzed, and the number of particles that should be deleted from the 80uL blood sample is determined based on the pulse width information. Different sample sizes correspond to different numbers of particles to be deleted. With a fixed sample size, the number of particles to be deleted can be fixed.
  • Step 403b Under a predetermined blood sample volume, determine the number of particles to be cut based on the pulse width information to obtain particle distribution information after the number of particles is cut.
  • the amount of blood sample to be tested each time is fixed, such as 80uL, so in this case, the number of particles to be deleted is also fixed, and the deleted particles can be directly determined according to the pulse width information number. .
  • Step 404 Correct the particle distribution information after deleting the number of particles according to a preset modification rule.
  • the method for correcting the particle distribution information after the number of particles is deleted according to a preset correction rule includes the particle distribution information after the number of particles is deleted according to a correction coefficient or a preset function method.
  • the specific process will not be described in detail.
  • the particle distribution information after particle number reduction according to the correction coefficient method please refer to steps 203-204 (including steps 204a and 204b); the particle distribution after particle number reduction according to the preset function method
  • the particle distribution after particle number reduction according to the preset function method refer to step 205 (including steps 204a and 204b).
  • the preset correction rule is to set at least two pulse width interval ranges, and the particle distribution information after the number of particles is reduced according to each pulse width interval range, the corresponding correction is based on the blood sample volume and pulse width
  • the information determines the number of pruned particles, or when the number of pruned particles is determined based on the pulse width information under a predetermined blood sample volume, the corresponding number of pruned particles within each pulse width interval may be an empirical value.
  • the corresponding number of particles to be deleted is determined according to the blood sample size and pulse width information, or in a predetermined blood sample
  • the setting corresponding to the pulse width information of the preset function determines the reference function of the number of particles to be cut.
  • the method for correcting blood cell parameters provided by the present invention is applied to a scenario where the particle distribution information after the number of particles is cut is corrected according to a preset function according to a preset correction rule.
  • the blood sample detector performs a test on the blood sample
  • the WBC particle distribution information in the blood sample is obtained by processing, and the overlapping particles of WBC particles with a pulse width information less than or equal to 25 ms are preset to be 0, and the overlapping particles of WBC particles with a pulse width information greater than 25 ms need to be deleted
  • the total number of pulse widths present in the particle is a test on the blood sample.
  • a sample is collected, the reference value of WBC is 6.72 ⁇ 10. ⁇ 9/L, and the count value given by the white blood cell channel after the test of the BC-6000 instrument produced by Shenzhen Mindray Biomedical Co., Ltd. is 3.72 ⁇ 10. ⁇ 9/L, the white blood cell channel is 45% lower than the reference value.
  • the microscopic examination confirmed that WBC aggregation occurred in the sample.
  • Figure 6 shows an example of the fluorescence-forward scattering light scattering point of the WBC aggregate sample.
  • Another blood cell parameter correction method provided by the present invention is applied to set at least two pulse width interval ranges according to a preset correction rule, and according to each pulse width interval range, the particle distribution information after the number of particles is cut is correspondingly The modified scene
  • the blood sample detector processes the blood sample to obtain the WBC particle distribution information in the blood sample, using the preset pulse width interval range set ((0, 25), (25, 33), (33, 41) , (41, 49), (49, 57) divide the WBC particle distribution information in the blood sample into 6 regions of particle distribution information, and determine the particle distribution information within the pulse width interval range 0-25ms as a haploid region Particle distribution information
  • the particle distribution information within the pulse width interval range of 25-33ms is the diploid area particle distribution information
  • the particle distribution information within the pulse width interval range 33-41ms is the triploid area particle distribution information
  • the particle distribution information within 41-49 ms is the particle distribution information of the tetraploid region
  • a sample is collected, the reference value of WBC is 6.72 ⁇ 10. ⁇ 9/L, and the count value given by the white blood cell channel after the test of the BC-6000 instrument produced by Shenzhen Mindray Biomedical Co., Ltd. is 3.72 ⁇ 10. ⁇ 9/L, the white blood cell channel is 45% lower than the reference value.
  • the microscopic examination confirmed that WBC aggregation occurred in the sample.
  • Figure 6 shows an example of the fluorescence-forward scattering light scattering point of the WBC aggregate sample.
  • Figure. The number of particles in the particle distribution information of the haploid area is counted, and the number of particles is 2115.
  • the particle distribution information of the diploid area, the particle distribution information of the triploid area, the particle distribution information of the tetraploid area, and the pentaploid area are respectively counted.
  • the number of particles in the particle distribution information and the particle distribution information in the hexaploid region, the particle number in the diploid region is 215, the particle number in the triploid region is 110, the particle number in the tetraploid region is 10, and the particle number in the pentploid region is Is 5, and the number of particles in the polyploid region is 2 for hexaploid and above, and the number of particles in the diploid region is 174, the number of particles in the triploid region is 70, four times
  • the number of particles in the body region is 5, the number of particles in the pentploid region is 2, and the number of particles in the hexaploid and above polyploid regions is 1.
  • the number of polyploid particles after the compensation calculation by the above formula is 2160, the total number of particles is 4275, the corresponding WBC value is 6.72 ⁇ 10. ⁇ 9/L, which basically corresponds to the reference value, and the correction is considered correct. It should be noted that, for the explanation of the same steps or concepts in this embodiment as in other embodiments, reference may be made to the descriptions in other embodiments, which will not be repeated here.
  • the blood cell parameter correction method obtained by the embodiment of the present invention obtains the light signal information of the particles in the blood sample, and divides the particles in the blood sample according to the pulse width information in the light signal information to obtain the particle distribution information.
  • the set correction rule corrects the particle distribution information to obtain the corrected particle distribution information.
  • the particle distribution information in the blood sample is corrected by the preset correction rule, which solves the problem of inaccurate number of blood cells due to particle aggregation when counting blood cells in the related art, and improves the statistics of the number of blood cells
  • the accuracy simplifies the operation process of blood cell number statistics and improves the degree of intelligence of blood cell number detection equipment.
  • the embodiments of the present invention provide a blood sample detector 5, which can be applied to the embodiments corresponding to FIGS. 1-2, 8, 11-12, 15, 17 and refer to FIG. 18
  • the blood sample detector may include: at least one reaction cell 51, an optical detection device 52, a delivery device 53, and a processor 54, wherein:
  • the reaction cell 51 is used to provide a reaction place for blood samples and reagents to prepare a sample solution.
  • the blood sample obtained by blood collection may be diluted and labeled with a fluorescent staining reagent to obtain a sample solution.
  • fluorescent staining reagents can be Pyronin, Acridine Orange and Thiazole Orange.
  • the optical detection device 52 is used to irradiate the blood sample treated with the reagent, that is, the above-mentioned sample liquid, to collect the optical signal generated by the light irradiation of each particle in the blood sample treated with the reagent and convert it into an electrical signal, To output optical signal information (ie, optical signal value).
  • the optical signal here may be a forward scattered light signal (FSC), a side scattered light signal (SSC), and a fluorescent scattered light signal (SFL, referred to herein as a fluorescent signal).
  • the optical detection device 52 may include, but is not limited to, a light source 521 and a sheath flow chamber 522 with an orifice 5221.
  • Particles in the blood sample may flow in the sheath flow chamber 522 and pass through the orifice 5221 and the light source 521 one by one.
  • the emitted light can illuminate the particles in the orifice 5221 and correspondingly generate scattered light signals and/or fluorescent signals.
  • the optical detection device 52 may further include a lens group 523, a photoelectric sensor 524 (such as a photodiode, a photomultiplier tube, etc.) and an A/D converter provided in front and side of the aperture, respectively, and the A/D converter may be provided in An element is formed in the processor 54 or separately, so that the lens group 523 can capture corresponding scattered light signals and fluorescent signals, and the photoelectric sensor 524 can convert the captured optical signals (referred to as scattered light signals and fluorescent signals, etc.) into electrical signals. Then, the A/D converter processes the electrical signal to obtain a digital signal through A/D conversion, and the digital signal can be output as optical signal information.
  • a photoelectric sensor 524 such as a photodiode, a photomultiplier tube, etc.
  • A/D converter provided in front and side of the aperture, respectively, and the A/D converter may be provided in An element is formed in the processor 54 or separately, so that the lens group 523 can capture corresponding scattered light signals and fluorescent signals, and the
  • the conveying device 53 is used to convey the sample liquid, which is a blood sample processed in the reaction cell 51, to the optical detection device 52.
  • the processor 54 is configured to receive and process the optical signal information output by the optical detection device 52 to obtain the cell parameters of the blood sample. Among them, the processor 54 obtains the optical signal information of the particles in the blood sample; divides the particles in the blood sample according to the pulse width information in the optical signal information to obtain the particle distribution information; and corrects the particle distribution information according to the preset correction rules to obtain The corrected particle distribution information; where the correction rule is related to the pulse width information in the optical signal.
  • the optical signal information includes forward scattered light information.
  • the light signal information includes side scattered light information and/or fluorescence signal information.
  • the correction rules stored in the processor 54 include:
  • the particle distribution information is corrected accordingly.
  • the processor 54 is also used to execute a stored blood cell parameter correction program to achieve the following steps:
  • Each correction coefficient is used to correct the corresponding number of particles in each pulse width interval range.
  • the correction rules stored in the processor 54 include:
  • the particle distribution information is modified accordingly according to a preset function; where the preset function is an increasing function with pulse width information as a variable.
  • the correction rule stored in the processor 54 includes:
  • the particle distribution information is corrected accordingly according to the correction coefficient; where the correction coefficient is positively correlated with the pulse width information.
  • the processor 54 is also used to execute a stored blood cell parameter correction program to achieve the following steps:
  • the processor 54 is also used to execute a stored blood cell parameter correction program to achieve the following steps:
  • the preset pruning rules stored in the processor 54 include:
  • the number of particles to be cut is determined based on the pulse width information to obtain particle distribution information after the number of particles is cut.
  • the reduced number of particles is inversely related to the pulse width information.
  • the processor 54 is also used to execute a stored blood cell parameter correction program to achieve the following steps:
  • the processor 54 is also used to execute a stored blood cell parameter correction program to achieve the following steps:
  • the processor 54 is also used to execute a stored blood cell parameter correction program to achieve the following steps:
  • the processor 54 is also used to execute a stored blood cell parameter correction program to achieve the following steps:
  • the number of particles is determined and/or output according to the corrected particle distribution information.
  • the processor 54 is used to identify and remove the bleeding shadow particles from the acquired particle light signal information, and then obtain WBC particles.
  • the blood sample detector provided in the embodiment of the present invention obtains the light signal information of the particles in the blood sample, and divides the particles in the blood sample according to the pulse width information in the light signal information to obtain the particle distribution information, and finally according to the preset
  • the correction rules of the particle are used to modify the particle distribution information to obtain the corrected particle distribution information.
  • the particle distribution information in the blood sample is corrected by preset correction rules, which solves the problem of inaccurate number of blood cells counted in the related art when counting blood cells, and improves the accuracy of counting blood cells,
  • the operation process of blood cell number statistics is simplified, and the degree of intelligence of blood cell number detection equipment is improved.
  • embodiments of the present invention provide a computer-readable storage medium that stores one or more statistical programs, and the one or more statistical programs may be executed by one or more processors to Implement the following steps:
  • the particle distribution information is corrected according to a preset correction rule to obtain the corrected particle distribution information; wherein, the correction rule is related to the pulse width information in the light signal information.
  • the optical signal information includes forward scattered light information.
  • the light signal information includes side scattered light information and/or fluorescence signal information.
  • the correction rules include:
  • the particle distribution information is corrected accordingly.
  • the correction rules include:
  • Each correction coefficient is used to correct the corresponding number of particles in each pulse width interval range.
  • the correction rule further includes:
  • the particle distribution information is modified accordingly according to a preset function; where the preset function is an increasing function with pulse width information as a variable.
  • the correction rules include:
  • the particle distribution information is corrected accordingly according to the correction coefficient; where the correction coefficient is positively correlated with the pulse width information.
  • the optical signal information includes fluorescent signal information
  • the particle distribution information is corrected according to a preset correction rule, including:
  • modifying the particle distribution information according to a preset modification rule includes:
  • the number of particles is deleted according to a preset deletion rule to obtain particle distribution information after the reduced number of particles, including:
  • the number of particles to be cut is determined based on the pulse width information to obtain particle distribution information after the number of particles is cut.
  • the reduced number of particles is inversely related to the pulse width information.
  • it further includes:
  • it further includes:
  • the method further includes:
  • it further includes:
  • the number of particles is determined and/or output according to the corrected particle distribution information.
  • the method further includes: identifying and removing the bleeding shadow particles from the obtained particle light signal information, and then obtaining WBC particles.
  • the blood cell parameter correction method provided by the embodiment of the present invention obtains the light signal information of the particles in the blood sample, and divides the particles in the blood sample according to the pulse width information in the light signal information to obtain the particle distribution information.
  • the set correction rule corrects the particle distribution information to obtain the corrected particle distribution information.
  • the particle distribution information in the blood sample is corrected by preset correction rules, which solves the problem of inaccurate number of blood cells counted in the related art when counting blood cells, and improves the accuracy of counting blood cells,
  • the operation process of blood cell number statistics is simplified, and the degree of intelligence of blood cell number detection equipment is improved.

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Abstract

一种血液细胞参数修正方法，该方法包括：获取血液样本中的粒子的光信号信息；根据该光信号信息中的脉宽信息划分该血液样本中的粒子，得到粒子分布信息；根据预设的修正规则对该粒子分布信息进行修正，得到修正后的粒子分布信息；其中，该修正规则与该光信号信息中的脉宽信息相关，以及一种执行该方法的血液样本检测仪(5)、存储有执行该方法的程序的存储介质。

Description

一种血液细胞参数修正方法、血液样本检测仪和存储介质 技术领域
本发明涉及医学检测技术领域，尤其涉及一种血液细胞参数修正方法、血液样本检测仪和存储介质。
背景技术
目前在医学检测领域中，血常规检测已成为确诊疾病时参考的一种常规医疗手段，血常规检测通常采用医用粒子分析仪例如血液细胞分析仪来实现。进行血常规检测时，可以采用血液细胞分析仪对白细胞(White Blood Cell，WBC)、红细胞、血小板、有核红细胞、网织红细胞等细胞进行分类及计数。
但是对不同类别的细胞进行数量统计的现有技术方案中，在血样的采集及制备过程中，可能会出现粒子聚集或粒子重叠等现象，例如红细胞粒子或白细胞粒子都可能出现这两种现象。例如对白细胞数量进行统计时，在血样的采集及制备过程中，会出现WBC粒子聚集现象以及WBC粒子重叠现象，导致统计获得的WBC数量值偏低，影响临床医生的判断。正常情况下，WBC粒子是均匀分布在血液中的。但是在血样的采集或制备过程中，可能会遇到WBC聚集成一团的现象。例如，在文献《50例白细胞聚集导致血常规检测时白细胞假性降低分析》(杨坚，贵州省惠水县人民医院，吉林医学2014年7月第35卷第20期)中有如下描述：“EDTA抗凝血可导致白细胞之间或白细胞与血小板之间发生聚集，传染性单核细胞增多症以及急性细菌感染使得白细胞之间的排斥力减弱等都可以导致白细胞的聚集，造成白细胞假性降低。白细胞聚集通常会导致白细胞假性降低，影响诊断的正确性，必须提高认识，不能完全依赖细胞仪检测的结果，尽量避免被 各种原因导致的白细胞降低所误导。”而WBC粒子重叠是指多个WBC粒子一个紧跟着一个经过测量孔的情况，基于该多个WBC粒子产生的脉宽信号使得检测设备将该多个WBC粒子识别为一个体积较大的WBC粒子。
粒子聚集现象以及粒子重叠现象，会导致细胞粒子计数不够准确，例如WBC粒子聚集现象以及WBC粒子重叠现象，会导致WBC粒子计数不够准确，进而影响临床医生的判断。
发明内容
有鉴于此，本发明实施例期望提供一种血液细胞参数修正方法、血液样本检测仪和存储介质，解决了相关技术中统计血液细胞时，统计的血液细胞的数量不准确的问题。
为达到上述目的，本发明实施例的技术方案是这样实现的：
一种血液细胞参数修正方法，所述方法包括：
获取血液样本中的粒子的光信号信息；
根据所述光信号信息中的脉宽信息划分所述血液样本中的粒子，得到粒子分布信息；
根据预设的修正规则对所述粒子分布信息进行修正，得到修正后的粒子分布信息；其中，所述修正规则与所述光信号信息中的脉宽信息相关。
可选的，所述光信号信息包括前向散射光信息。
可选的，所述光信号信息包括侧向散射光信息和/或荧光信号信息。
可选的，所述修正规则包括：
设置至少两个脉宽区间范围；
根据每一所述脉宽区间范围对所述粒子分布信息进行相应的修正。
可选的，所述修正规则包括：
设置至少两个脉宽区间范围，每一所述脉宽区间范围对应相应的修正系数；其中，所述修正系数与所述脉宽信息正相关；
采用每一所述修正系数修正对应的每一所述脉宽区间范围的粒子数量。
可选的，所述修正规则包括：
根据预设函数对所述粒子分布信息进行相应的修正；其中，所述预设函数是以所述脉宽信息为变量的增函数。
可选的，所述修正规则包括：
根据预设函数确定修正系数；
根据所述修正系数对所述粒子分布信息进行相应的修正；其中，所述修正系数与所述脉宽信息正相关。
可选的，所述光信号信息包括荧光信号信息，所述根据预设的修正规则对粒子分布信息进行修正，包括：
筛去荧光信号值低于预设阈值的粒子，得到筛后的粒子分布信息；
根据预设的修正规则对筛后的粒子分布信息进行修正。
可选的，所述根据预设的修正规则对粒子分布信息进行修正，包括：
根据预设删减规则删减粒子数，得到删减粒子数后的粒子分布信息；
根据预设的修正规则对删减粒子数后的粒子分布信息进行修正。
可选的，所述预设删减规则包括：
根据血液样本量和脉宽信息确定删减的粒子数量，得到删减粒子数后的粒子分布信息；
或者，在预定的血液样本量下，根据脉宽信息确定删减的粒子数量，得到删减粒子数后的粒子分布信息。
可选的，删减的粒子数与脉宽信息负相关。
可选的，还包括：
输出修正后的粒子分布信息。
可选的，还包括：
输出修正前和修正后的粒子分布信息。
可选的，根据预设的修正规则对粒子分布信息进行修正之后，还包括：
发出粒子分布信息已经过修正的提示；和/或
根据修正幅度发出粒子聚集的提示和/或报警。
可选的，还包括：
根据所述修正后的粒子分布信息确定和/或输出粒子数量。
可选的，获取血液样本中的粒子的光信号信息之后，还包括：
从所获取的粒子光信号信息中识别出血影粒子并去除，然后得到WBC粒子。
一种血液样本检测仪，包括：
至少一个反应池，用于为血液样本与试剂提供反应场所；
光学检测装置，用于对经试剂处理后的血液样本进行光照射，收集所述经试剂处理后的血液样本中各粒子因光照射所产生的光学信号，并转换成电信号，以输出光学信号信息；
输送装置，用于将所述反应池中经试剂处理后的血液样本输送到所述光学检测装置中；
处理器，用于接收并处理所述光学检测装置输出的光学信号信息，以得到血液样本的测量参数；其中，所述处理器获取血液样本中的粒子的光信号信息；根据所述光信号信息中的脉宽信息划分所述血液样本中的粒子，得到粒子分布信息；根据预设的修正规则对所述粒子分布信息进行修正得到修正后的粒子分布信息；其中，所述修正规则与所述光信号中的脉宽信息相关。
可选的，所述光信号信息包括前向散射光信息。
可选的，所述光信号信息包括侧向散射光信息和/或荧光信号信息。
可选的，所述处理器中存储的所述修正规则包括：
设置至少两个脉宽区间范围；
根据每一所述脉宽区间范围对所述粒子分布信息进行相应的修正。
可选的，所述处理器用于：
设置至少两个脉宽区间范围，每一所述脉宽区间范围对应相应的修正系数；其中，所述修正系数与所述脉宽信息正相关；
采用每一所述修正系数修正对应的每一所述脉宽区间范围的粒子数量。
可选的，所述处理器中存储的所述修正规则包括：
根据预设函数对所述粒子分布信息进行相应的修正；其中所述预设函数是以所述脉宽信息为变量的增函数。
可选的，所述处理器中存储的所述修正规则包括：
根据预设函数确定修正系数；
根据所述修正系数对所述粒子分布信息进行相应的修正；其中，所述修正系数与所述脉宽信息正相关。
可选的，所述处理器用于：
筛去荧光信号值低于预设阈值的粒子，得到筛后的粒子分布信息；
根据预设的修正规则对筛后的粒子分布信息进行修正。
可选的，所述处理器用于：
根据预设删减规则删减粒子数，得到删减粒子数后的粒子分布信息；
根据预设的修正规则对删减粒子数后的粒子分布信息进行修正。
可选的，所述处理器中存储的所述预设删减规则包括：
根据血液样本量和脉宽信息确定删减的粒子数量，得到删减粒子数后的粒子分布信息；
或者，在预定的血液样本量下，根据脉宽信息确定删减的粒子数量，得到删减粒子数后的粒子分布信息。
可选的，删减的粒子数与脉宽信息负相关。
可选的，所述处理器还用于：
输出修正后的粒子分布信息。
可选的，所述处理器还用于：
输出修正前和修正后的粒子分布信息。
可选的，根据预设的修正规则对粒子分布信息进行修正之后，所述处理器还用于：
发出粒子分布信息已经过修正的提示；和/或
根据修正幅度发出粒子聚集的提示和/或报警。
可选的，所述处理器还用于：
根据所述修正后的粒子分布信息确定和/或输出粒子数量。
可选的，所述处理器用于：从所获取的粒子光信号信息中识别出血影粒子并去除，然后得到WBC粒子。
一种计算机可读存储介质，所述计算机可读存储介质其上存储有血液细胞参数的修正程序，所述血液细胞参数的修正程序被处理器执行时实现上述任一项所述的血液细胞参数修正方法的步骤。
本发明的实施例所提供的血液细胞参数修正方法、血液样本检测仪和计算机可读存储介质，获取血液样本中的粒子的光信号信息，并根据光信号信息中的脉宽信息划分血液样本中的粒子，得到粒子分布信息，最后根据预设的修正规则对粒子分布信息进行修正，得到修正后的粒子分布信息。这样，通过预设的修正规则对血液样本中的粒子分布信息进行修正，解决了相关技术中统计血液细胞时，统计的血液细胞的数量不准确的问题，提高了统计血液细胞数量的准确度，简化了血液细胞数量统计的操作过程，并提高了血液细胞数量检测设备的智能化程度。
附图说明
图1为本发明实施例提供的一种血液细胞参数修正方法的流程示意图；
图2为本发明实施例提供的另一种血液细胞参数修正方法的流程示意图；
图3为本发明实施例提供的一种光学流动室的结构示意图；
图4为本发明实施例提供的一种脉宽的示意图；
图5为本发明实施例提供的一种脉冲面积示意图；
图6为本发明实施例提供的一种应用场景示意图；
图7为本发明实施例提供的另一种应用场景示意图；
图8为本发明实施例提供的又一种血液细胞参数修正方法的流程示意图；
图9为本发明实施例提供的又一种应用场景示意图；
图10为本发明实施例提供的再一种应用场景示意图；
图11为本发明实施例提供的再一种血液细胞参数修正方法的流程示意图；
图12为本发明另一实施例提供的一种血液细胞参数修正方法的流程示意图；
图13为本发明另一实施例提供的一种应用场景示意图；
图14为本发明另一实施例提供的一种应用场景示意图；
图15为本发明另一实施例提供的另一种血液细胞参数修正方法的流程示意图；
图16为本发明另一实施例提供的又一种应用场景示意图；
图17为本发明另一实施例提供的又一种血液细胞参数修正方法的流程示意图；
图18为本发明实施例提供的一种血液样本检测仪的结构示意图。
具体实施方式
以下结合附图及实施例，对本发明进行进一步详细说明。应当理解，此处所提供的实施例仅仅用以解释本发明，并不用于限定本发明。另外，以下所提供的实施例是用于实施本发明的部分实施例，而非提供实施本发明的全部实施例，在不冲突的情况下，本发明实施例记载的技术方案可以任意组合的方式实施。
需要说明的是，在本发明实施例中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的方法或者装置不仅包括所明确记载的要素，而且还包括没有明确列出的其他要素，或者是还包括为实施方法或者装置所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括该要素的方法或者装置中还存在另外的相关要素(例如方法中的步骤或者装置中的单元，这里的单元可以是部分电路、部分处理器、部分程序或软件等等)。
需要说明的是，本发明实施例所涉及的术语“第一\第二\第三”仅仅是区别类似的对象，不代表针对对象的特定排序，可以理解地，“第一\第二\第三”在允许的情况下可以互换特定的顺序或先后次序。应该理解“第一\第二\第三”区分的对象在适当情况下可以互换，以使这里描述的本发明的实施例能够以除了在这里图示或描述的那些以外的顺序实施。
本发明的实施例提供一种血液细胞参数修正方法，参照图1所示，该方法包括以下步骤：
步骤101、获取血液样本中的粒子的光信号信息。
其中，光信号信息可以包括前向散射光信息、和/或侧向散射光信息和/或荧光信号信息。也即光信号信息可以仅仅包括前向散射光信息、侧向散射光信息和荧光信号信息中的一种信息，也可以是它们的任意组合。
在本发明实施例中，步骤101“获取血液样本中的粒子的光信号信息”可以由血液样本检测仪来实现。血液样本中的粒子可以是指血液样本中的所有类型的细胞粒子，例如可以包括血液样本中的WBC、红细胞、血小板、有核红细胞、网织红细胞等细胞粒子。光信号信息可以包括对血液样本粒子进行区分识别的光信号的特征信息，例如采用光信号对血液样本粒子进行处理后，检测血液样本粒子对应的光信号的脉宽或者光信号的脉冲峰值等。
采集血液样本，并对血液样本采用化学试剂进行处理；然后对采用化 学试剂进行处理后的血液样本采用激光散射法进行处理，其中，光信号可以包括前向散射光(Forward Scatter，FSC)、侧向散射光(Side Scatter，SSC)和荧光(Fluorescence，FL)等三种光信号，其中，可以采用FSC检测粒子的大小，SSC检测粒子内部结构的复杂程度，FL检测粒子内的例如脱氧核糖核酸(Deoxyribonucleic Acid，DNA)和核糖核酸(Ribonucleic Acid，RNA)等可被荧光染料染色物质的含量，这样，对血液样本中的粒子采用上述激光进行处理后，可以检测到经过血液样本中的粒子后的光信号信息，例如相应光信号的脉宽信息等。
在血液中，不同种类的粒子之间，粒子的大小、内部结构、可被荧光染料染色物质含量并不相同，因此可以通过反映粒子的光信号信息进行不同种类粒子的区分，例如从粒子中区分出红细胞、白细胞、血小板等等。对于白细胞而言，白细胞还可以细分为中性粒细胞、淋巴细胞、嗜酸性粒细胞、嗜碱性粒细胞和单核细胞这五种细胞。因此，可以通过光信号信息区分不同种类的粒子。
由于血液样本中不同大小的粒子对应的光信号的脉宽信息不同，所以可以根据光信号信息中的脉宽信息区分血液样本中不同大小的粒子，并统计血液样本中各种大小粒子的数量。因此，对于某一种类的细胞，可以采用光信号的脉宽信息区分不同大小的细胞，从而方便统计细胞数量，例如WBC细胞的数量。
步骤102、根据光信号信息中的脉宽信息划分粒子，得到粒子分布信息。
在本发明实施例中，步骤102“根据光信号信息中的脉宽信息划分粒子，得到粒子分布信息”可以由血液样本检测仪来实现。血液样本检测仪根据获取到的光信号信息中的脉宽信息对血液样本中的粒子进行划分，将血液样本中的粒子确定出来，并得到血液样本中的粒子的分布信息。例如在识别出某一种类的粒子后，根据脉宽信息对该种类的粒子进行划分，从而得到该种类粒子的粒子分布信息，例如WBC粒子随脉宽的分布信息、红细胞粒 子随脉宽的分布信息、血小板粒子随脉宽的分布信息、有核红细胞粒子随脉宽的分布信息、网织红细胞粒子随脉宽的分布信息。在以下说明中，主要以WBC粒子随脉宽的分布信息为例进行说明。
在其中一个实施例中，如果是修正WBC粒子的分布信息，在步骤101之后，可以从所获取的粒子光信号信息中识别出血影粒子(GHOST粒子)并去除掉，然后得到WBC粒子。再根据光信号信息中的脉宽信息划分WBC粒子，得到WBC粒子分布信息。可以从所获取的粒子光信号信息中的FSC/SSC/FL三维信号识别出血影粒子，也可以从所获取的粒子光信号信息中的脉宽信息识别出血影粒子，在此不做具体限定。
步骤103、根据预设的修正规则对粒子分布信息进行修正，得到修正后的粒子分布信息。
其中，修正规则与光信号信息中的脉宽信息相关。
在本发明实施例中，步骤103“根据预设的修正规则对粒子分布信息进行修正，得到修正后的粒子分布信息”可以由血液样本检测仪来实现。预设的修正规则是根据粒子重叠和/或粒子聚集的特征来确定的，这样，采用预设的修正规则对粒子分布信息进行修正，从而修正粒子数量，解决因粒子重叠和/或粒子聚集导致粒子数量偏低的情况，使最终修正得到的血液样本中的粒子的数量与实际数量更加相符。
本发明的实施例所提供的血液细胞参数修正方法，获取血液样本中的粒子的光信号信息，并根据光信号信息中的脉宽信息划分血液样本中的粒子，得到粒子分布信息，最后根据预设的修正规则对粒子分布信息进行修正，得到修正后的粒子分布信息。这样，通过预设的修正规则对血液样本中的粒子分布信息进行修正，解决了相关技术中统计血液细胞(例如白细胞)时，统计的血液细胞的数量不准确的问题，提高了统计血液细胞数量的准确度，简化了血液细胞数量统计的操作过程，并提高了血液细胞数量检测设备的智能化程度。
基于前述实施例，在本发明其他实施例中，血液样本检测仪执行步骤103后还可以选择执行步骤A或步骤B或步C或步骤D：
步骤A、输出修正后的粒子分布信息。
在本发明实施例中，血液样本检测仪对血液样本的粒子分布信息根据预设的修正规则进行修正得到修正后的粒子分布信息后，可以将修正后的粒子分布信息通过血液样本检测仪的显示器输出显示。其中，可以采用散点图、数据阵列、散点图结合数据阵列等方式将修正后的粒子分布信息显示在血液样本检测仪的显示器上。
步骤B、输出修正前和修正后的粒子分布信息。
在本发明实施例中，血液样本检测仪对血液样本的粒子分布信息根据预设的修正规则进行修正得到修正后的粒子分布信息后，可以将修正前的粒子分布信息即步骤102中得到的粒子分布信息，和修正后的粒子分布信息即步骤103中得到的修正后的粒子分布信息显示在血液样本检测仪的显示器上。其中，可以采用散点图、数据阵列、散点图结合数据阵列等方式在血液样本检测仪的显示器上显示修正前的粒子分布信息和修正后的粒子分布信息。
步骤C、发出粒子分布信息已经过修正的提示；和/或根据修正幅度发出粒子聚集的提示和/或报警。
在本发明实施例中，血液样本检测仪对血液样本的粒子分布信息根据预设的修正规则进行修正得到修正后的粒子分布信息后，可以生成提示使用血液样本检测仪的用户对血液样本的粒子分布信息已进行修正的提示信息，例如“WBC粒子信息已进行修正”。其中该提示信息可以直接在血液样本检测仪的显示器上进行显示，或者血液样本检测仪也可以将该提示信息发送至与血液样本检测仪具有通信连接的移动终端设备上。或者，可以根据修正幅度发出粒子聚集的提示和/或报警，或者可以根据修正幅度发出粒子聚集程度的提示和/或报警，例如发出“粒子聚集”“粒子聚集程度过高” 等提示信息或者在显示器上发出视觉警报。可以根据修正幅度来判断粒子聚集程度，修正幅度越高，聚集程度越高。修正幅度，可以根据修正前的粒子数量和修正后的粒子数量之间的关系进行判断，例如根据两者的比例关系或差值关系。
步骤D、根据修正后的粒子分布信息确定和/或输出粒子数量。
在本发明实施例中，血液样本检测仪对血液样本的粒子分布信息根据预设的修正规则进行修正得到修正后的粒子分布信息后，对修正后的粒子分布信息中的粒子数量进行统计，得到血液样本中的粒子的实际数量即粒子数量。或者，血液样本得到粒子数量后可以将粒子数量显示在血液样本检测仪的显示器上。
基于前述实施例，本发明的实施例提供一种血液细胞参数修正方法，应用于血液样本检测仪，参照图2所示，该方法包括以下步骤：
步骤201、获取血液样本中的粒子的光信号信息。
其中，光信号信息可以包括前向散射光信息、和/或侧向散射光信息和/或荧光信号信息。也即光信号信息可以仅仅包括前向散射光信息、侧向散射光信息和荧光信号信息中的一种信息，也可以是它们的任意组合。
在本发明实施例中，以光信号信息包含有FSC信息为例进行说明。
确定血液样本中不同的粒子时，通常可以通过血液样本中的粒子大小等方式来实现。其中，血液样本中的粒子的大小可以用粒子通过血液样本检测仪中的光学流动室的测量孔的时间t来表示，如图3中所示，光学流动室G的长度为L，假设待检测的血液样本中的粒子Y在光学流动室中的流动速率为u，图3中的箭头方向表示血液样本中的粒子Y的流动方向，则该粒子通过该光学流动室的时间t可以用一下公式进行计算得到：t＝(L+D)/u，其中，D表示该细胞粒子的直径。因此，血液样本检测仪对血液样本中的粒子的大小进行测定可以通过记录血液样本中的粒子通过光 学流动室的时间来实现，具体为：当血液样本中的粒子通过光学流动室的测量孔时，激发血液样本检测仪发出脉冲信号，直至血液样本中的粒子完全通过光学流动室，得到的脉冲信号可以如图4所示，其中：横坐标为粒子通过该光学流动室的时间t，单位为毫秒(ms)，纵坐标为脉冲强度；A为脉冲峰值，即是从基线到脉冲最大值的脉冲强度值；B为脉冲宽度(简称为脉宽)，可以用于表示血液样本中的粒子通过光学流动室的测量孔的实际时间。如图4，脉冲宽度可以是脉冲强度曲线与预设脉冲强度阈值所表示直线两个相交点之间的时间宽度。在图4中，脉冲峰值A约为800，对应的脉冲宽度B约为25ms。基于前述粒子通过该光学流动室的时间t的计算公式可知，当光学流动室中的血液样本的流动速率一定时，流过光学流动室的测量孔的粒子越大，则粒子通过光学流动室的测量孔的时间越长，对应的脉宽也越大。其中，当血液样本中的粒子例如WBC聚集时，由于是两个或多个WBC聚集到一起通过光学流动室的测量孔的，所以检测得到的血液样本中的粒子直径会比正常的一个WBC粒子的直径大，导致通过光学流动室的测量孔的时间变长，对应的脉宽变大。
在本发明实施例中，血液样本中的粒子的脉宽信息可以是前向散射光的脉宽(Forward Scattered light pulse Width，FSCW)，也可以是侧向散射光的脉宽(Side Scatter light pulse Width，SSCW)，还可以是荧光的脉宽(Fluorescence light pulse Width，FLW)。需说明的是，脉宽也可以用脉冲的面积来代替，可以是FSC、SSC、FL三种光中的任意一种光的脉冲面积，其中，脉冲面积具体可以如图5中的C所示，为脉冲强度曲线与脉冲强度阈值的第一个交点对应的横坐标t1和最后一个交点对应的横坐标t2之间脉冲强度曲线所围成的面积。
步骤202、根据光信号信息中的脉宽信息划分血液样本中的粒子，得到粒子分布信息。
具体的，由于不同的血液样本中的粒子对应的脉宽信息不同，所以可 以根据不同的光信号信息中的脉宽信息划分血液样本中的粒子，得到每一类型粒子对应的粒子分布信息，例如得到的WBC粒子的分布信息如图6所示，其中，图6中横坐标表示脉宽，纵坐标表示前向散射光的脉冲峰值，图中的每一个黑点代表一个WBC粒子。
步骤203、获取预先设置的至少两个脉宽区间范围。
在本发明实施例中，预先设置的至少两个脉宽区间范围可以是根据大量实验分析得到的经验理论值，可在实际应用过程中不断进行矫正。
步骤204、根据脉宽区间范围对粒子分布信息进行相应的修正，得到修正后的粒子分布信息。
其中，修正规则与光信号信息中的脉宽信息相关。
在本发明实施例中，根据设置的至少两个脉宽区间范围对得到的粒子分布信息进行划分，将粒子划分为至少两个区域的粒子，并对不同区域的粒子数量进行统计，然后根据设置的至少两个脉宽区间范围对应的修正系数对对应的区域的粒子数量进行修正，即可得到修正后的粒子分布信息。
示例性的，血液样本检测仪中存储的修正规则中预先设置的脉宽区间范围可以为两个，为一倍体脉宽范围和多倍体脉宽范围，即根据一倍体脉宽范围和多倍体脉宽范围将粒子分布信息划分为一倍体粒子分布区域和多倍体粒子分布区域，这样可以对这两个粒子分布区域分别采用各自对应的方法进行修正，即可得到修正后的粒子分布信息。
血液样本检测仪中存储的修正规则中预先设置的脉宽区间范围也可以多于两个，例如为六个，分别为一倍体脉宽范围、二倍体脉宽范围、三倍体脉宽范围、四倍体脉宽范围、五倍体脉宽范围和六倍体脉宽范围，即根据这六个预先设置的脉宽范围将粒子分布信息划分为一倍体粒子分布区域、二倍体粒子分布区域、三倍体粒子分布区域、四倍体粒子分布区域、五倍体粒子分布区域和六倍体粒子分布区域，这样可以对这两个粒子分布区域分别采用各自对应的方法进行修正，即可得到修正后的粒子分布信息。
其中，一倍体脉宽范围是指单个细胞粒子通过光学流动室时所测得的脉宽，即粒子直径为一个粒子直径(一倍粒子直径)时对应的脉宽范围。当多个细胞粒子通过光学流动室时，粒子直径为两倍粒子直径时对应的脉宽范围为二倍体脉宽范围，同理，三倍体脉宽范围为三倍粒子直径对应的脉宽范围，四倍体脉宽范围为四倍粒子直径对应的脉宽范围，五倍体脉宽范围为五倍粒子直径对应的脉宽范围，六倍体脉宽范围为六倍粒子直径对应的脉宽范围等等，以此类推。需说明的是，两倍粒子直径、三倍粒子直径、四倍粒子直径、五倍粒子直径和六倍粒子直径等是由于细胞聚集的原因而出现的，通常2个细胞粒子聚集、3个细胞粒子聚集、4个细胞粒子聚集直至8个细胞粒子聚集都可能会出现两倍粒子直径的情况，其中，如图7所示为2个细胞粒子聚集、3个细胞粒子聚集、4个细胞粒子聚集和8个细胞粒子聚集出现两倍粒子直径的示意图。上述的一倍体脉宽范围、二倍体脉宽范围、……六倍体脉宽范围、多倍体脉宽范围都可以为经验值。
基于前述实施例，本发明其他实施例提供的一种血液细胞参数修正方法，应用于血液样本检测仪，参照图8所示，血液样本检测仪执行存储的修正规则时，执行的步骤204具体可以由以下步骤204a-204b来实现，其中修正规则为：设置至少两个脉宽区间范围，每一所述脉宽区间范围对应相应的修正系数；其中，所述修正系数与所述脉宽信息正相关；采用每一所述修正系数修正对应的每一所述脉宽区间范围的粒子数量。
步骤204a、确定每一脉宽区间范围对应的修正系数。
其中，修正系数与脉宽正相关。
在本发明实施例中，修正系数与脉宽正相关也即修正系数根据脉宽的变化而变化，例如修正系数随着脉宽区间范围的变大而变大。例如第一脉宽区间范围为(a，b)，对应着一个修正系数，例如为第一修正系数；第二脉宽区间范围为(b，c)，对应着另一个修正系数，例如为第二修正系数；第三脉宽区间范围为(c，d)，对应着又一个修正系数，例如为第三修正系 数；其中，a<b<c<d，对应的，第一修正系数小于或等于第二修正系数，第二修正系数小于或等于第三修正系数。
每一脉宽区间范围对应的修正系数是预先设置的，其可以是一个经验值，也可以是一个经验公式。
示例性的，基于WBC粒子分布信息设置两个以上的脉宽区间范围例如如图9所示为六个脉宽区间范围时，每一脉宽区间范围对应的粒子分布信息具体为：脉宽区间范围0～25ms内的粒子分布信息G1为一倍体区域粒子分布信息，脉宽区间范围25～33ms内的粒子分布信息H1为二倍体区域粒子分布信息，脉宽区间范围33～41ms内的粒子分布信息I1为三倍体区域粒子分布信息，脉宽区间范围41～49ms内的粒子分布信息J1为四倍体区域粒子分布信息，脉宽区间范围49～57ms内的粒子分布信息K1为五倍体区域粒子分布信息，脉宽区间范围57～65ms内的粒子分布信息L1为六倍体区域粒子分布信息。其中，一倍体是指直径为一个细胞粒子直径的细胞粒子，由于细胞聚集和重叠的原因，存在两倍体、三倍体、四倍体、五倍体和六倍体等。对应的基于WBC一倍体区域粒子分布信息、二倍体区域粒子分布信息、三倍体区域粒子分布信息、四倍体区域粒子分布信息、五倍体区域粒子分布信息和六倍体区域粒子分布信息设置的修正系数为经验值即常数，依次为1、3、10、20、30、40，修正系数与脉宽正相关。
需说明的是，在实际应用过程中，可以采用如图9中所示的等脉宽的划分方式进行脉宽区间范围的划分；还可以采用如图10中所示的采用不等脉宽的划分方式进行脉宽区间范围的划分。
步骤204b、采用每一修正系数修正对应的每一脉宽区间范围的粒子数量。
在本发明实施例中，统计每一脉宽区间范围内的粒子数量，然后每一修正系数乘以对应的每一脉宽区间范围内的粒子数量即可实现对每一脉宽区间范围内的粒子数量的修正。
在一个实施例中，收集一例样本，其中WBC的参考值为6.72×10.^9/L，经过深圳迈瑞生物医疗股份有限公司生产的BC-6000仪器测试后白细胞通道给出的计数值为3.72×10.^9/L，白细胞通道对比参考值偏低了45％，经过镜检确认该样本发生了WBC聚集，如图6所示为一例发生了WBC聚集样本的荧光-前向散射光散点图。对图10所示的不同脉宽区间范围内的粒子数量进行统计，可以得到一倍体区域粒子分布信息G2对应的粒子数量为2115个，二倍体区域粒子分布信息H2对应的粒子数量为215个，三倍体区域粒子分布信息I2对应的粒子数量为110个，四倍体区域粒子分布信息J2对应的粒子数量为10，五倍体区域粒子分布信息K2对应的粒子数量为5，六倍体区域粒子分布信息L2对应的粒子数量为2；若针对图10的六个脉宽范围设置的修正系数与图9的六个脉宽范围设置的修正系数相同，则采用步骤204a中对应的修正系数对不同脉宽范围的粒子数量进行修正，得到一倍体区域粒子分布信息G2修正后的粒子数量为2115×1＝2115个，二倍体区域粒子分布信息H2修正后的粒子数量为215×3＝645个，三倍体区域粒子分布信息I2修正后的粒子数量为110×10＝1100个，四倍体区域粒子分布信息J2修正后的粒子数量为10×20＝200个，五倍体区域粒子分布信息K2对应的第一细胞样本的第三数量为5×30＝150个，六倍体区域粒子分布信息L2修正后的粒子数量为2×40＝80个；对上述不同脉宽范围内的区域粒子分布信息进行累加，可以确定图6中WBC粒子的实际数量为4290，对应WBC值为6.73×10.^9/L，与参考值6.72×10.^9/L对应，认为修正基本正确。
基于前述实施例，本发明其他实施例提供的一种血液细胞参数修正方法，应用于血液样本检测仪，参照图11所示，血液样本检测仪执行步骤202后，还可以选择执行步骤205来实现：
步骤205、根据预设函数对粒子分布信息进行相应的修正。
其中，预设函数是以脉宽信息为变量的增函数，根据函数计算结果(因 变量)对粒子分布信息进行相应的修正。预设函数可以是以脉宽信息为变量、以修正系数为因变量的函数，也即函数计算结果可以是根据脉宽变大而变大的修正系数，然后再根据修正系数对粒子分布信息中对应脉宽所对应的粒子数量进行修正，例如将修正系数乘以对应脉宽的粒子数量，得到对应脉宽修正后的粒子数量。当然预设函数也可以是以脉宽信息和对应脉宽所对应的粒子数量为变量、以修正系数为因变量的函数。
在本发明实施例中，预设函数是与脉宽信息相关的一个预设函数，是一个经验公式。
在本发明其他实施例中，参照图12所示，血液样本检测仪执行步骤205时，具体可以由以下步骤205a-205b来实现：
步骤205a、根据预设函数确定修正系数。
在本发明实施例中，预设函数可以是一个与脉宽信息相关的分段函数。
示例性的，WBC粒子分布信息在脉宽信息小于或等于25ms时，对应的预设函数为一个预设常数，例如为1，对应的脉宽信息大于25ms时，为一个与脉宽信息相关的预设函数。其中，采用对应的脉宽信息大于25ms时的预设函数进行计算的过程为步骤a-b：
步骤a、分别计算每一脉宽信息与第一预设系数的乘积，得到第一数值。
在本发明实施例中，第一数值x j＝a×w j进行计算得到。其中，a表示第一预设系数，通常为一个常数，是一个经验值，在不同的应用场景中可以根据实际应用场景发生改变，也可以不断的进行矫正。在本发明实施例中，a可以为0.925，w表示是每一脉宽信息。也就是说，基于预设函数，可以将图6中的WBC粒子分布信息分为如图13所示的粒子分布信息，即图13E区域(脉宽信息小于或等于25ms)中对应的修正系数是一个常数，一般设置为1，w j可以是图13F区域(脉宽信息大于25ms)内分布的粒子的每一脉宽，j的取值为正整数，假设对图13F区域对应的脉宽进行统计，共有 n个，则j的取值为1，2……，n。
步骤b、计算第一数值与第二预设系数的和值，得到对应的修正系数。
在本发明实施例中，每一脉宽信息对应的细胞粒子样本的修正系数可以记为y j＝x j+b。其中，b为第二预设系数，为一个经验值，在不同的应用场景中可以根据实际应用场景发生改变，也可以不断的进行矫正。示例性的，在本发明实施例中，针对图13F区域内的粒子的修正系数的计算，b取值可以是-24.75，对应的每一脉宽信息对应的细胞粒子样本的修正系数的计算公式，即大于25ms时的预设函数可以记为y j＝0.925w j-24.75。
步骤205b、根据修正系数对粒子分布信息进行相应的修正。
其中，修正系数与脉宽信息正相关。
在本发明实施例中，统计脉宽信息小于或等于25ms区域内的WBC粒子的数量，将脉宽信息小于或等于25ms区域内的WBC粒子的数量与针对脉宽信息小于或等于25ms区域设置的修正系数相乘，得到脉宽信息小于或等于25ms区域内的WBC粒子的实际数量；统计脉宽信息大于25ms区域内每一脉宽对应的WBC粒子的数量，并根据公式y j＝0.925w j-24.75计算每一脉宽对应的修正系数，然后计算每一脉宽对应的修正系数与每一脉宽对应的WBC粒子的数量的乘积，得到每一脉宽对应的WBC粒子的实际数量，最后计算每一脉宽对应的WBC粒子的实际数量的累加和，得到脉宽信息大于25ms区域内的WBC粒子的数量。
在一个实施例中，收集一例样本，其中WBC的参考值为6.72×10.^9/L，经过深圳迈瑞生物医疗股份有限公司生产的BC-6000仪器测试后白细胞通道给出的计数值为3.72×10.^9/L，白细胞通道对比参考值偏低了45％，经过镜检确认该样本发生了WBC聚集，如图6所示为一例发生了WBC聚集样本的荧光-前向散射光散点图。对图13E中一倍体脉宽范围内的粒子数量进行统计并修正得到实际粒子数量为2115个，并采用上述大于25ms时的 预设函数公式对图13F中多倍体脉宽范围内的粒子数量255进行修正后得到实际粒子数量为2160个，因此，实际总粒子数量为4275，对应WBC值为6.71×10.^9/L，与参考值6.72×10.^9/L基本对应，认为修正正确。
其中，设置预设函数的过程可以是：确定每一脉宽区间范围内粒子聚集的平均值，具体确定粒子聚集的平均值的公式可以为：
Figure PCTCN2018125095-appb-000001
其中，i为每一脉宽区间范围内粒子聚集时出现的粒子聚集的个数。例如WBC粒子出现两倍粒子直径的聚集的情况，假设从2个WBC粒子聚集到8个WBC粒子聚集细胞等概率出现，采用上述公式进行计算可以得到两倍体脉宽范围内WBC粒子聚集个数的平均值为5个，因此，在粒子发生聚集的情况下，统计二倍体脉宽范围内WBC粒子聚集的实际数量时，可以采用二倍体脉宽范围内统计到的WBC粒子数量乘以5倍的系数。同理，可以计算得到三倍体脉宽范围内WBC粒子聚集个数的平均值为15个，四倍体脉宽范围内WBC粒子聚集个数的平均值为25个，五倍体脉宽范围内WBC粒子聚集个数的平均值为35个，六倍及以上脉宽范围内WBC粒子聚集个数的平均值为45个。由于WBC粒子聚集与WBC粒子重叠现象会出现在同一个区域内，对WBC粒子聚集产生干扰，为此可以适当降低两倍体脉宽范围及以上对应的聚集粒子数，可以采用拟合的方式适当降低作为修正系数的平均值。实验数据表明，检测到的一倍体、二倍体、三倍体、四倍体、五倍体、六倍体粒子数的平均脉宽约为18、30、40、50、60、70。进行拟合时，拟合的曲线为大致通过由脉宽-修正系数所组成的(x,y)这些点为标准，其中x为脉宽值，y为每一脉宽范围对应的修正系数，如二倍体区域的点为(30,5)，三倍体区域的点为(40,15)等。拟合可以采用直线拟合的方式，或者二次曲线等形式。一种线性拟合的粒子补偿曲线如图14所示，图中脉宽在27到70区间内有五个控制点，分别为(30,3)、(40,10)、(50,20)、(60,30)、(70,40)，在此区间内采用直线拟合的方式生成一条连续聚集粒子补偿系数的修正直 线对应的函数即可用于对聚集粒子进行修正。
需要说明的是，本实施例中与其它实施例中相同步骤或概念的解释可以参考其它实施例中的描述，此处不再赘述。
本发明的实施例所提供的血液细胞参数修正方法，获取血液样本中的粒子的光信号信息，并根据光信号信息中的脉宽信息划分血液样本中的粒子，得到粒子分布信息，最后根据预设的修正规则对粒子分布信息进行修正，得到修正后的粒子分布信息。这样，通过预设的修正规则对血液样本中的粒子分布信息进行修正，解决了相关技术中统计血液细胞时，由于粒子聚集和重叠等导致统计的血液细胞的数量不准确的问题，提高了统计血液细胞数量的准确度，简化了血液细胞数量统计的操作过程，并提高了血液细胞数量检测设备的智能化程度。
基于前述实施例，本发明的实施例提供一种血液细胞参数修正方法，应用于血液样本检测仪，参照图15所示，该方法包括以下步骤：
步骤301、获取血液样本中的粒子的光信号信息。
其中，光信号信息包括荧光信号信息。
在本发明实施例中，对应的光信号信息包括FL信号信息和FSC信息，或者包括FL信号信息和SSC信息，或者包括FL信号信息、FSC信息和SSC信息，或者包括FL信号信息和其他光信号信息。
示例性的，采用FL信号和激光信号对血液样本进行染色处理，得到具有FL信号信息和FSC信息的血液样本中的粒子的分布信息。
步骤302、根据光信号信息中的脉宽信息划分血液样本中的粒子，得到粒子分布信息。
步骤303、筛去荧光信号值低于预设阈值的粒子，得到筛后的粒子分布信息。
在本发明实施例中，以出现两倍粒子直径情况为例说明粒子聚集与其他情况(如粒子重叠)的不同。当发生粒子重叠时，通常只是两个粒子重 叠，三个粒子以上重叠的概率极低，因此对应的产生的FL信号强度大概是两个粒子FL信号强度之和。但是当发生粒子聚集时，不只是两个粒子的聚集产生两倍粒子直径，8个粒子也会产生两倍的粒子直径，平均下来大约是5个粒子，对应的FL信号强度平均也是五倍的粒子FL强度。所以发生粒子聚集时的FL强度会比粒子重叠等其他情况产生的FL信号强度大。所以，增加FL信号强度的限制这一条件，可以排除其他情况(如粒子重叠)对粒子聚集时统计的实际粒子分布信息的干扰。因此，对于上述的多倍体区域，例如上述脉宽大于25ms的区域，可以筛去荧光信号值低于预设阈值的粒子。当然，一倍体区域，例如上述脉宽小于25ms的区域也可以筛去荧光信号值低于预设阈值的粒子，只是该区域出现荧光信号值低于预设阈值的粒子会较少。对图6的散点图中的多倍体区域，在筛去荧光信号值低于预设阈值的粒子后，得到筛后的粒子分布信息可以如图16所示，其中，横坐标为脉宽，单位时间为ms，纵坐标为前向散射光。
预设阈值是经验值，在不同的应用场景中，对应的预设阈值不同。例如预设阈值为3500。当然，这个预设阈值可以是固定值，也可以是根据不同样本而不同，可以人工设定或机器判断后设定。
步骤304、根据预设的修正规则对筛后的粒子分布信息进行修正。
对应的，本发明提供的一种血液细胞参数修正方法，可以是血液样本检测仪对血液样本进行荧光处理和激光处理后，确定血液样本中的WBC粒子分布信息，并从WBC粒子分布信息中筛去FL信号的信号值低于预设阈值3500的WBC粒子，得到筛后的WBC粒子分布信息；采用预设函数对筛后的WBC粒子分布信息进行处理的，具体为：脉宽信息小于或等于25ms的筛后的WBC粒子的修正系数为c＝1.0，脉宽信息大于25ms的筛后的WBC粒子的修正系数的预设函数计算公式为c＝w-25，其中，w为多倍体中的细胞样本的脉宽。
在一个实施例中，收集一例样本，WBC的参考值为6.72×10.^9/L，经 过深圳迈瑞生物医疗股份有限公司生产的BC-6000仪器测试后白细胞通道给出的计数值为3.72×10.^9/L，白细胞通道对比参考值偏低了45％，经过镜检确认该样本发生了WBC聚集，如图6所示为一例发生了WBC聚集样本的荧光-前向散射光散点图，通过计算，脉宽大于25ms的粒子有255个，筛后的粒子数为150个，通过预设函数计算公式c＝w-25对粒子数进行修正，得到脉宽信息大于25ms的修正后的WBC粒子的实际数量为2170个；对应的，脉宽信息小于或等于25ms的筛后的WBC粒子的实际数量2170加上脉宽信息大于25ms的筛后的WBC粒子的实际数量2115个，即可得到血液样本中WBC粒子的实际数量为4285个，对应WBC值为6.73×10.^9/L，与参考值6.72×10.^9/L基本对应，认为修正正确。
预设的修正规则，例如所包括的预设函数，是考虑了筛减的粒子数的情况下设定的。例如上述筛减的粒子数为255-150＝105，这部分粒子是被筛减的，会对最后统计粒子数量造成影响，因此在设定修正规则时可以考虑这个因素。当然，由于影响并不大，在一些实施例中也可以忽略这部分筛减粒子的影响。筛减的粒子都可认为是粒子重叠的粒子，对于粒子重叠的情况，业界都有相应的计算规则，设定修正规则时可以将这些计算规则考虑进来。
对应的，本发明提供的另一种血液细胞参数修正方法，可以是血液样本检测仪对血液样本进行荧光处理和激光处理后，确定血液样本中的WBC粒子分布信息，并从WBC粒子分布信息中筛去携带FL信号的信号值低于预设阈值3500的WBC粒子，得到筛后的WBC粒子分布信息；设置至少两个脉宽区间范围，根据脉宽区间范围对筛后的WBC粒子分布信进行相应的修正的具体过程为：采用预设脉宽区间范围(0，25)，(25，33)，(33，41)，(41，49)，(49，57)将筛后的WBC粒子分布信息分为6个区域的粒子分布信息，并确定脉宽区间范围0～25ms内的粒子分布信息为一倍体区域粒子分布信息，脉宽区间范围25～33ms内的粒子分布信息为二倍体区域粒 子分布信息，脉宽区间范围33～41ms内的粒子分布信息为三倍体区域粒子分布信息，脉宽区间范围41～49ms内的粒子分布信息为四倍体区域粒子分布信息，脉宽区间范围49～57ms内的粒子分布信息为五倍体区域粒子分布信息，脉宽区间范围57～64ms内的粒子分布信息为六倍体区域粒子分布信息；获取针对每一脉宽区间范围预先设置的修正系数，修正系数和对应的脉宽区间范围为：(1，一倍体)，(5，二倍体)，(13，三倍体)，(25，四倍体)，(35，五倍体)，(45，六倍体)。
在一个实施例中，收集一例样本，WBC的参考值为6.72×10.^9/L，经过深圳迈瑞生物医疗股份有限公司生产的BC-6000仪器测试后白细胞通道给出的计数值为3.72×10.^9/L，白细胞通道对比参考值偏低了45％，经过镜检确认该样本发生了WBC聚集，如图6所示为一例发生了WBC聚集样本的荧光-前向散射光散点图。通过统计，样本一倍体区域粒子数为2115个，二倍体区域粒子数为215，三倍体区域粒子数为110，四倍体区域粒子数为10，五倍体区域粒子数为5，六倍体及以上多倍体区域粒子数为2。对二倍体以上区域进行筛减后，二倍体区域粒子分布信息对应的筛后WBC粒子数量176，三倍体区域粒子分布信息对应的筛后WBC粒子数量为80，四倍体区域粒子分布信息对应的筛后WBC粒子数量为5，五倍体区域粒子分布信息对应的筛后WBC粒子数量为2，六倍体区域粒子分布信息对应的筛后WBC粒子数量为1；分别计算每一脉宽区间范围内的筛后WBC粒子数量与对应的每一脉宽区间范围的修正系数的乘积，即可得到一倍体区域粒子分布信息对应的筛后WBC粒子实际数量为2115，二倍体区域粒子分布信息对应的筛后WBC粒子实际数量为880，三倍体区域粒子分布信息对应的筛后WBC粒子实际数量为1040，四倍体区域粒子分布信息对应的筛后WBC粒子实际数量为125，五倍体区域粒子分布信息对应的筛后WBC粒子实际数量为70，六倍体区域粒子分布信息对应的筛后WBC粒子实际数量为45；最后，血液样本中WBC粒子的实际数量为每一脉宽区间范围内 对应的筛后WBC粒子实际数量的累加和，为4275个，对应WBC值为6.71×10.^9/L，与参考值6.72×10.^9/L基本对应，认为修正正确。
同样，预设的修正规则，是考虑了筛减的粒子数的情况下设定的。这部分粒子是被筛减的，会对最后统计粒子数量造成影响，因此在设定修正规则时可以考虑这个因素。当然，由于影响并不大，在一些实施例中也可以忽略这部分筛减粒子的影响。
需要说明的是，本实施例中与其它实施例中相同步骤或概念的解释可以参考其它实施例中的描述，此处不再赘述。
本发明的实施例所提供的血液细胞参数修正方法，获取血液样本中的粒子的光信号信息，并根据光信号信息中的脉宽信息划分血液样本中的粒子，得到粒子分布信息，最后根据预设的修正规则对粒子分布信息进行修正，得到修正后的粒子分布信息。这样，通过预设的修正规则对血液样本中的粒子分布信息进行修正，解决了相关技术中统计血液细胞时，由于粒子重叠导致统计的血液细胞的数量不准确的问题，提高了统计血液细胞数量的准确度，简化了血液细胞数量统计的操作过程，并提高了血液细胞数量检测设备的智能化程度。
基于前述实施例，本发明的实施例提供一种血液细胞参数修正方法，应用于血液样本检测仪，主要针对细胞样本存在聚集和重叠的情况，参照图17所示，该方法包括以下步骤401～步骤403：
步骤401、获取血液样本中的粒子的光信号信息。
步骤402、根据光信号信息中的脉宽信息划分血液样本中的粒子，得到粒子分布信息。
步骤403、根据预设删减规则删减粒子数，得到删减粒子数后的粒子分布信息。
在本发明实施例中，预设删减规则是根据粒子发生重叠的特性来确定 的。以两倍体粒子直径为例说明需根据预设删减规则删减粒子数的原因：两个粒子发生重叠时，产生的脉宽约是一个粒子产生脉宽的1.5倍。但是当发生粒子聚集时，两到8个粒子发生粒子聚集均可以产生两倍粒子的脉宽，对应的产生的脉宽也是一个粒子产生脉宽的1.5倍。所以在脉宽上粒子重叠和粒子聚集会叠加到一块，所以需要排除粒子重叠对粒子统计时的干扰。
在本发明其他实施例中，步骤403可以由步骤403a或者步骤403b来实现：
步骤403a、根据血液样本量和脉宽信息确定删减的粒子数，得到删减粒子数后的粒子分布信息。
其中，删减的粒子数与脉宽负相关。
在本发明实施例中，删减的粒子数与脉宽负相关也即删减的粒子根据脉宽的变化而变化，例如删减的粒子数量随着脉宽区间范围的变大而变少。例如在设定的血液样本量下，第一脉宽区间范围为(a，b)，对应着一个设定的需要删减的粒子数量，例如为第一删减粒子数量；第二脉宽区间范围为(b，c)，对应着另一个设定的需要删减的粒子数量，例如为第二删减粒子数量；第三脉宽区间范围为(c，d)，对应着又一个设定的需要删减的粒子数量，例如为第三删减粒子数量；其中，a<b<c<d，对应的，第一删减的粒子大于或等于第二删减粒子数量，第二删减粒子数量大于或等于第三删减粒子数量。
血样样本量是指采集到的进行测试的血液样本量，例如，若采集到35微升(uL)血液样本，则对35uL血液样本进行分析，根据脉宽信息确定这35uL血液样本应该删减的粒子数量，若采集到的是80uL血液样本，则对80uL血液样本进行分析，根据脉宽信息确定这80uL血液样本应该删减的粒子数量。不同的样本量对应需要删减的粒子数量并不一样，在固定样本量的情况下，需要删减的粒子数量可以固定。
步骤403b、在预定的血液样本量下，根据脉宽信息确定删减的粒子数， 得到删减粒子数后的粒子分布信息。
在本发明实施例中，每次进行测试的血液样本量是固定的，例如80uL，因此在这种情况下，需要删减的粒子数也是固定的，可以直接根据脉宽信息确定删减的粒子数。。
步骤404、根据预设的修正规则对删减粒子数后的粒子分布信息进行修正。
在本发明实施例中，根据预设的修正规则对删减粒子数后的粒子分布信息进行修正的方法包括根据修正系数或者预设函数的方法对删减粒子数后的粒子分布信息。具体过程不在详细赘述，根据修正系数的方法对删减粒子数后的粒子分布信息可以参照步骤203-204(包括步骤204a和204b)；根据预设函数的方法对删减粒子数后的粒子分布信息可以参照步骤205(包括步骤204a和204b)。
其中，当预设的修正规则是设置至少两个脉宽区间范围，根据每一脉宽区间范围对删减粒子数后的粒子分布信息进行相应的修正时，对应的根据血液样本量和脉宽信息确定删减的粒子数量，或者在预定的血液样本量下，根据脉宽信息确定删减的粒子数量时，对应的每一脉宽区间范围内的删减的粒子数量可以是经验值。
当预设的修正规则是根据预设函数对删减粒子数后的粒子分布信息进行相应的修正时，对应的根据血液样本量和脉宽信息确定删减的粒子数量，或者在预定的血液样本量下，根据脉宽信息确定删减的粒子数量时，与预设函数的脉宽信息对应的设置确定需删减的粒子数量的参考函数。
本发明提供的一种血液细胞参数修正方法，应用于根据预设的修正规则是根据预设函数对删减粒子数后的粒子分布信息进行相应的修正的场景，血液样本检测仪对血液样本进行处理得到血液样本中的WBC粒子分布信息，预先设置脉宽信息小于或等于25ms的WBC粒子的重叠粒子即需要删减的粒子数量为0，脉宽信息大于25ms的WBC粒子的重叠粒子即需要删 减的粒子数量的计算公式为α k＝-1.25w k+81.25，w k为脉宽信息大于25ms的WBC粒子中第k个脉宽值，k取值从1到脉宽信息大于25ms的WBC粒子中存在的脉宽总数量。
在一个实施例中，收集一例样本，WBC的参考值为6.72×10.^9/L，经过深圳迈瑞生物医疗股份有限公司生产的BC-6000仪器测试后白细胞通道给出的计数值为3.72×10.^9/L，白细胞通道对比参考值偏低了45％，经过镜检确认该样本发生了WBC聚集，如图6所示为一例发生了WBC聚集样本的荧光-前向散射光散点图。通过计算，脉宽大于25ms的粒子有342个，通过上述的公式α k＝-1.25w k+81.25进行删减，然后再通过预设函数计算公式c k＝1.1w k-30对粒子数进行修正，得到脉宽信息大于25ms的修正后的WBC粒子的实际数量为2170个；对应的，脉宽信息小于或等于25ms的筛后的WBC粒子的实际数量2170加上脉宽信息大于25ms的筛后的WBC粒子的实际数量2115个，即可得到血液样本中WBC粒子的实际数量为4285个，对应WBC值为6.73×10.^9/L，与参考值6.72×10.^9/L基本对应，认为修正正确
本发明提供的另一种血液细胞参数修正方法，应用于根据预设的修正规则是设置至少两个脉宽区间范围，根据每一脉宽区间范围对删减粒子数后的粒子分布信息进行相应的修正的场景，血液样本检测仪对血液样本进行处理得到血液样本中的WBC粒子分布信息，采用预设脉宽区间范围集合((0，25)，(25，33)，(33，41)，(41，49)，(49，57)将血液样本中的WBC粒子分布信息分为6个区域的粒子分布信息，并确定脉宽区间范围0～25ms内的粒子分布信息为一倍体区域粒子分布信息，脉宽区间范围25～33ms内的粒子分布信息为二倍体区域粒子分布信息，脉宽区间范围33～41ms内的粒子分布信息为三倍体区域粒子分布信息，脉宽区间范围41～49ms内的粒子分布信息为四倍体区域粒子分布信息，脉宽区间范围 49～57ms内的粒子分布信息为五倍体区域粒子分布信息，脉宽区间范围57～64ms内的粒子分布信息为六倍体区域粒子分布信息；获取预先设置的重叠粒子即需删减的粒子数量依次为0、41、40、5、3、1。
在一个实施例中，收集一例样本，WBC的参考值为6.72×10.^9/L，经过深圳迈瑞生物医疗股份有限公司生产的BC-6000仪器测试后白细胞通道给出的计数值为3.72×10.^9/L，白细胞通道对比参考值偏低了45％，经过镜检确认该样本发生了WBC聚集，如图6所示为一例发生了WBC聚集样本的荧光-前向散射光散点图。对一倍体区域粒子分布信息的粒子数量进行统计，得到粒子数量为2115，分别统计二倍体区域粒子分布信息、三倍体区域粒子分布信息、四倍体区域粒子分布信息、五倍体区域粒子分布信息、六倍体区域粒子分布信息中的粒子数量，得到二倍体区域粒子数为215，三倍体区域粒子数为110，四倍体区域粒子数为10，五倍体区域粒子数为5，六倍体及以上多倍体区域粒子数为2，分别按照上述的删减数量进行删减后，得到二倍体区域粒子数为174，三倍体区域粒子数为70，四倍体区域粒子数为5，五倍体区域粒子数为2，六倍体及以上多倍体区域粒子数为1。经过上述公式进行补偿计算后的多倍体粒子数为2160个，总粒子数为4275，对应WBC值为6.72×10.^9/L，与参考值基本对应，认为修正正确。需要说明的是，本实施例中与其它实施例中相同步骤或概念的解释可以参考其它实施例中的描述，此处不再赘述。
本发明的实施例所提供的血液细胞参数修正方法，获取血液样本中的粒子的光信号信息，并根据光信号信息中的脉宽信息划分血液样本中的粒子，得到粒子分布信息，最后根据预设的修正规则对粒子分布信息进行修正，得到修正后的粒子分布信息。这样，通过预设的修正规则对血液样本中的粒子分布信息进行修正，解决了相关技术中统计血液细胞时，由于粒子聚集统计的血液细胞的数量不准确的问题，提高了统计血液细胞数量的准确度，简化了血液细胞数量统计的操作过程，并提高了血液细胞数量检 测设备的智能化程度。
基于前述实施例，本发明的实施例提供一种血液样本检测仪5，该血液样本检测仪可以应用于图1-2、8、11-12、15、17对应的实施例中，参照图18所示，该血液样本检测仪可以包括：至少一个反应池51、光学检测装置52、输送装置53及处理器54，其中：
反应池51，用于为血液样本与试剂提供反应场所，以制备成样本液。具体地，可对采血所得血液样本经稀释并用荧光染色试剂进行标记，得到样本液。常用的荧光染色试剂可以是派若宁、吖啶橙和噻唑橙等。
光学检测装置52，用于对经试剂处理后的血液样本即上述的样本液进行光照射，收集经试剂处理后的血液样本中各粒子因光照射所产生的光学信号，并转换成电信号，以输出光学信号信息(即光信号值)。这里的光学信号可以是前向散射光信号(FSC)、侧向散射光信号(SSC)、荧光散射光信(SFL，本文简称荧光信号)。光学检测装置52的可以但不仅限于包括光源521和具有孔口5221的鞘流流动室522等，血液样本中的粒子可在鞘流流动室522内流动，并逐个经过孔口5221，光源521所发出的光可照射到孔口5221中的粒子并对应产生散射光信号和/或荧光信号。光学检测装置52还可以包括分别在孔口前方和侧向设置的透镜组523、光电感应器524(如光电二极管、光电倍增管等)及A/D转换器，A/D转换器可设置在处理器54中或单独形成一个元件，从而透镜组523可捕捉对应散射光信号和荧光信号，光电感应器524可将捕捉到的光学信号(指散射光信号和荧光信号等)转换为电信号，再A/D转换器将电信号经A/D转换处理得到数字信号，可以将该数字信号作为光学信号信息输出。
输送装置53，用于将反应池51中经试剂处理后的血液样本即样本液输送到光学检测装置52中。
处理器54，用于接收并处理光学检测装置52输出的光学信号信息，以 得到血液样本的细胞参数。其中，处理器54获取血液样本中的粒子的光信号信息；根据光信号信息中的脉宽信息划分血液样本中的粒子，得到粒子分布信息；根据预设的修正规则对粒子分布信息进行修正得到修正后的粒子分布信息；其中，修正规则与光信号中的脉宽信息相关。
在本发明其他实施例中，光信号信息包括前向散射光信息。
在本发明其他实施例中，光信号信息包括侧向散射光信息和/或荧光信号信息。
在本发明其他实施例中，处理器54中存储的修正规则包括：
设置至少两个脉宽区间范围；
根据每一脉宽区间范围对粒子分布信息进行相应的修正。
在本发明其他实施例中，处理器54还用于执行存储的血液细胞参数修正程序，以实现以下步骤：
设置至少两个脉宽区间范围，确定每一脉宽区间范围对应的修正系数；其中，修正系数与脉宽信息正相关；
采用每一修正系数修正对应的每一脉宽区间范围的粒子数量。
在本发明其他实施例中，处理器54中存储的修正规则包括：
根据预设函数对粒子分布信息进行相应的修正；其中预设函数是以脉宽信息为变量的增函数。
在本发明实施例中，处理器54中存储的修正规则包括：
根据预设函数确定修正系数；
根据修正系数对粒子分布信息进行相应的修正；其中，修正系数与脉宽信息正相关。
在本发明其他实施例中，处理器54还用于执行存储的血液细胞参数修正程序，以实现以下步骤：
筛去荧光信号值低于预设阈值的粒子，得到筛后的粒子分布信息；
根据预设的修正规则对筛后的粒子分布信息进行修正。
在本发明其他实施例中，处理器54还用于执行存储的血液细胞参数修正程序，以实现以下步骤：
根据预设删减规则删减粒子数，得到删减粒子数后的粒子分布信息；
根据预设的修正规则对删减粒子数后的粒子分布信息进行修正。
在本发明其他实施例中，处理器54中存储的预设删减规则包括：
根据血液样本量和脉宽信息确定删减的粒子数量，得到删减粒子数后的粒子分布信息；
或者，在预定的血液样本量下，根据脉宽信息确定删减的粒子数量，得到删减粒子数后的粒子分布信息。
在本发明其他实施例中，删减的粒子数与脉宽信息负相关。
在本发明其他实施例中，处理器54还用于执行存储的血液细胞参数修正程序，以实现以下步骤：
输出修正后的粒子分布信息。
在本发明其他实施例中，处理器54还用于执行存储的血液细胞参数修正程序，以实现以下步骤：
输出修正前和修正后的粒子分布信息。
在本发明其他实施例中，根据预设的修正规则对粒子分布信息进行修正之后，处理器54还用于执行存储的血液细胞参数修正程序，以实现以下步骤：
发出粒子分布信息已经过修正的提示；和/或根据修正幅度发出粒子聚集的提示和/或报警。
在本发明其他实施例中，处理器54还用于执行存储的血液细胞参数修正程序，以实现以下步骤：
根据修正后的粒子分布信息确定和/或输出粒子数量。
在本发明其他实施例中，处理器54用于：从所获取的粒子光信号信息中识别出血影粒子并去除，然后得到WBC粒子。
需说明的是，本实施例中处理器所实现的步骤之间的交互过程，可以参照图1-2、8、11-12、15、17对应的实施例及上述实施例提供的血液细胞参数修正方法中的交互过程，此处不再赘述。
本发明的实施例所提供的血液样本检测仪，获取血液样本中的粒子的光信号信息，并根据光信号信息中的脉宽信息划分血液样本中的粒子，得到粒子分布信息，最后根据预设的修正规则对粒子分布信息进行修正，得到修正后的粒子分布信息。这样，通过预设的修正规则对血液样本中的粒子分布信息进行修正，解决了相关技术中统计血液细胞时，统计的血液细胞的数量不准确的问题，提高了统计血液细胞数量的准确度，简化了血液细胞数量统计的操作过程，并提高了血液细胞数量检测设备的智能化程度。
基于前述实施例，本发明的实施例提供一种计算机可读存储介质，计算机可读存储介质存储有一个或者多个统计程序，一个或者多个统计程序可被一个或者多个处理器执行，以实现以下步骤：
获取血液样本中的粒子的光信号信息；
根据光信号信息中的脉宽信息划分血液样本中的粒子，得到粒子分布信息；
根据预设的修正规则对粒子分布信息进行修正，得到修正后的粒子分布信息；其中，修正规则与光信号信息中的脉宽信息相关。
在本发明其他实施例中，光信号信息包括前向散射光信息。
在本发明其他实施例中，光信号信息包括侧向散射光信息和/或荧光信号信息。
在本发明其他实施例中，修正规则包括：
设置至少两个脉宽区间范围；
根据每一脉宽区间范围对粒子分布信息进行相应的修正。
在本发明其他实施例中，修正规则包括：
设置至少两个脉宽区间范围，确定每一脉宽区间范围对应的修正系数； 其中，修正系数与脉宽信息正相关；
采用每一修正系数修正对应的每一脉宽区间范围的粒子数量。
在本发明其他实施例中，修正规则还包括：
根据预设函数对粒子分布信息进行相应的修正；其中，预设函数是以脉宽信息为变量的增函数。
在本发明其他实施例中，修正规则包括：
根据预设函数确定修正系数；
根据修正系数对粒子分布信息进行相应的修正；其中，修正系数与脉宽信息正相关。
在本发明其他实施例中，光信号信息包括荧光信号信息，根据预设的修正规则对粒子分布信息进行修正，包括：
筛去荧光信号值低于预设阈值的粒子，得到筛后的粒子分布信息；
根据预设的修正规则对筛后的粒子分布信息进行修正。
在本发明其他实施例中，根据预设的修正规则对粒子分布信息进行修正，包括：
根据预设删减规则删减粒子数，得到删减粒子数后的粒子分布信息；
根据预设的修正规则对删减粒子数后的粒子分布信息进行修正。
在本发明其他实施例中，根据预设删减规则删减粒子数，得到删减粒子数后的粒子分布信息，包括：
根据血液样本量和脉宽信息确定删减的粒子数量，得到删减粒子数后的粒子分布信息；
或者，在预定的血液样本量下，根据脉宽信息确定删减的粒子数量，得到删减粒子数后的粒子分布信息。
在本发明其他实施例中，删减的粒子数与脉宽信息负相关。
在本发明其他实施例中，还包括：
输出修正后的粒子分布信息。
在本发明其他实施例中，还包括：
输出修正前和修正后的粒子分布信息。
在本发明其他实施例中，根据预设的修正规则对粒子分布信息进行修正之后，还包括：
发出粒子分布信息已经过修正的提示；和/或根据修正幅度发出粒子聚集的提示和/或报警。
在本发明其他实施例中，还包括：
根据修正后的粒子分布信息确定和/或输出粒子数量。
在本发明其他实施例中，获取血液样本中的粒子的光信号信息之后，还包括：从所获取的粒子光信号信息中识别出血影粒子并去除，然后得到WBC粒子。
需说明的是，本实施例中处理器所实现的步骤之间的交互过程，可以参照图1-2、8、11-12、15、17对应的实施例及上述实施例提供的血液细胞参数修正方法中的交互过程，此处不再赘述。
以上，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应以权利要求的保护范围为准。
工业实用性
本发明的实施例所提供的血液细胞参数修正方法，获取血液样本中的粒子的光信号信息，并根据光信号信息中的脉宽信息划分血液样本中的粒子，得到粒子分布信息，最后根据预设的修正规则对粒子分布信息进行修正，得到修正后的粒子分布信息。这样，通过预设的修正规则对血液样本中的粒子分布信息进行修正，解决了相关技术中统计血液细胞时，统计的血液细胞的数量不准确的问题，提高了统计血液细胞数量的准确度，简化 了血液细胞数量统计的操作过程，并提高了血液细胞数量检测设备的智能化程度。

Claims (33)

  1. 一种血液细胞参数修正方法，其特征在于，所述方法包括：
    获取血液样本中的粒子的光信号信息；
    根据所述光信号信息中的脉宽信息划分所述血液样本中的粒子，得到粒子分布信息；
    根据预设的修正规则对所述粒子分布信息进行修正，得到修正后的粒子分布信息；其中，所述修正规则与所述光信号信息中的脉宽信息相关。
  2. 根据权利要求1所述的方法，其特征在于，所述光信号信息包括前向散射光信息。
  3. 根据权利要求1所述的方法，其特征在于，所述光信号信息包括侧向散射光信息和/或荧光信号信息。
  4. 根据权利要求1所述的方法，其特征在于，所述修正规则包括：
    设置至少两个脉宽区间范围，根据每一所述脉宽区间范围对所述粒子分布信息进行相应的修正。
  5. 根据权利要求4所述的方法，其特征在于，所述修正规则包括：
    设置至少两个脉宽区间范围，每一所述脉宽区间范围对应相应的修正系数；其中，所述修正系数与所述脉宽信息正相关；
    采用每一所述修正系数修正对应的每一所述脉宽区间范围的粒子数量。
  6. 根据权利要求1所述的方法，其特征在于，所述修正规则包括：
    根据预设函数对所述粒子分布信息进行相应的修正；其中，所述预设函数是以所述脉宽信息为变量的增函数。
  7. 根据权利要求6所述的方法，其特征在于，所述修正规则包括：
    根据预设函数确定修正系数；
    根据所述修正系数对所述粒子分布信息进行相应的修正；其中，所述修正系数与所述脉宽信息正相关。
  8. 根据权利要求1-7任一项所述的方法，其特征在于，所述光信号信息包括荧光信号信息，所述根据预设的修正规则对粒子分布信息进行修正，包括：
    筛去荧光信号值低于预设阈值的粒子，得到筛后的粒子分布信息；
    根据预设的修正规则对筛后的粒子分布信息进行修正。
  9. 根据权利要求1-7任一项所述的方法，其特征在于，所述根据预设的修正规则对粒子分布信息进行修正，包括：
    根据预设删减规则删减粒子数，得到删减粒子数后的粒子分布信息；
    根据预设的修正规则对删减粒子数后的粒子分布信息进行修正。
  10. 根据权利要求9所述的方法，其特征在于，所述预设删减规则包括：
    根据血液样本量和脉宽信息确定删减的粒子数量，得到删减粒子数后的粒子分布信息；
    或者，在预定的血液样本量下，根据脉宽信息确定删减的粒子数量，得到删减粒子数后的粒子分布信息。
  11. 根据权利要求10所述的方法，其特征在于，删减的粒子数与脉宽信息负相关。
  12. 根据权利要求1所述的方法，其特征在于，还包括：
    输出修正后的粒子分布信息。
  13. 根据权利要求1所述的方法，其特征在于，还包括：
    输出修正前和修正后的粒子分布信息。
  14. 根据权利要求1所述的方法，其特征在于，根据预设的修正规则对粒子分布信息进行修正之后，还包括：
    发出粒子分布信息已经过修正的提示；和/或
    根据修正幅度发出粒子聚集的提示和/或报警。
  15. 根据权利要求1所述的方法，其特征在于，还包括：
    根据所述修正后的粒子分布信息确定和/或输出粒子数量。
  16. 根据权利要求1-7、10-15任一所述的方法，其特征在于，获取血液样本中的粒子的光信号信息之后，还包括：
    从所获取的粒子光信号信息中识别出血影粒子并去除，然后得到WBC粒子。
  17. 一种血液样本检测仪，其特征在于，包括：
    至少一个反应池，用于为血液样本与试剂提供反应场所；
    光学检测装置，用于对经试剂处理后的血液样本进行光照射，收集所述经试剂处理后的血液样本中各粒子因光照射所产生的光学信号，并转换成电信号，以输出光学信号信息；
    输送装置，用于将所述反应池中经试剂处理后的血液样本输送到所述光学检测装置中；
    处理器，用于接收并处理所述光学检测装置输出的光学信号信息，以得到血液样本的测量参数；其中，所述处理器获取血液样本中的粒子的光信号信息；根据所述光信号信息中的脉宽信息划分所述血液样本中的粒子，得到粒子分布信息；根据预设的修正规则对所述粒子分布信息进行修正得到修正后的粒子分布信息；其中，所述修正规则与所述光信号中的脉宽信息相关。
  18. 根据权利要求17所述的血液样本检测仪，其特征在于，所述光信号信息包括前向散射光信息。
  19. 根据权利要求17所述的血液样本检测仪，其特征在于，所述光信号信息包括侧向散射光信息和/或荧光信号信息。
  20. 根据权利要求17所述的血液样本检测仪，其特征在于，所述处理器中存储的所述修正规则包括：
    设置至少两个脉宽区间范围；
    根据每一所述脉宽区间范围对所述粒子分布信息进行相应的修正。
  21. 根据权利要求20所述的血液样本检测仪，其特征在于，所述处理器用于：
    设置至少两个脉宽区间范围，每一所述脉宽区间范围对应相应的修正系数；其中，所述修正系数与所述脉宽信息正相关；
    采用每一所述修正系数修正对应的每一所述脉宽区间范围的粒子数量。
  22. 根据权利要求17所述的血液样本检测仪，其特征在于，所述处理器中存储的所述修正规则包括：
    根据预设函数对所述粒子分布信息进行相应的修正；其中所述预设函数是以所述脉宽信息为变量的增函数。
  23. 根据权利要求22所述的血液样本检测仪，其特征在于，所述处理器中存储的所述修正规则包括：
    根据预设函数确定修正系数；
    根据所述修正系数对所述粒子分布信息进行相应的修正；其中，所述修正系数与所述脉宽信息正相关。
  24. 根据权利要求17-23任一项所述的血液样本检测仪，其特征在于，所述处理器用于：
    筛去荧光信号值低于预设阈值的粒子，得到筛后的粒子分布信息；
    根据预设的修正规则对筛后的粒子分布信息进行修正。
  25. 根据权利要求17-23任一项所述的血液样本检测仪，其特征在于，所述处理器用于：
    根据预设删减规则删减粒子数，得到删减粒子数后的粒子分布信息；
    根据预设的修正规则对删减粒子数后的粒子分布信息进行修正。
  26. 根据权利要求25所述的血液样本检测仪，其特征在于，所述处理器中存储的所述预设删减规则包括：
    根据血液样本量和脉宽信息确定删减的粒子数量，得到删减粒子数后的粒子分布信息；
    或者，在预定的血液样本量下，根据脉宽信息确定删减的粒子数量，得到删减粒子数后的粒子分布信息。
  27. 根据权利要求26所述的血液样本检测仪，其特征在于，删减的粒子数与脉宽信息负相关。
  28. 根据权利要求17所述的血液样本检测仪，其特征在于，所述处理器还用于：
    输出修正后的粒子分布信息。
  29. 根据权利要求17所述的血液样本检测仪，其特征在于，所述处理器还用于：
    输出修正前和修正后的粒子分布信息。
  30. 根据权利要求17所述的血液样本检测仪，其特征在于，根据预设的修正规则对粒子分布信息进行修正之后，所述处理器还用于：
    发出粒子分布信息已经过修正的提示；和/或
    根据修正幅度发出粒子聚集的提示和/或报警。
  31. 根据权利要求17所述的血液样本检测仪，其特征在于，所述处理器还用于：
    根据所述修正后的粒子分布信息确定和/或输出粒子数量。
  32. 根据权利要求17-23、26-31任一所述的血液样本检测仪，其特征在于，所述处理器用于：从所获取的粒子光信号信息中识别出血影粒子并去除，然后得到WBC粒子。
  33. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质其上存储有血液细胞参数的修正程序，所述血液细胞参数的修正程序被处理器执行时实现权利要求1至16中任一项所述的血液细胞参数修正方法的步骤。
PCT/CN2018/125095 2018-12-28 2018-12-28 一种血液细胞参数修正方法、血液样本检测仪和存储介质 WO2020133285A1 (zh)

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