CN112654857A

CN112654857A - Method for processing detection value of measurement object, blood cell analyzer, and storage medium

Info

Publication number: CN112654857A
Application number: CN201880097223.0A
Authority: CN
Inventors: 叶波; 郑文波; 王官振; 陈鹏震
Original assignee: Shenzhen Mindray Bio Medical Electronics Co Ltd
Current assignee: Shenzhen Mindray Bio Medical Electronics Co Ltd
Priority date: 2018-12-28
Filing date: 2018-12-28
Publication date: 2021-04-13
Anticipated expiration: 2038-12-28
Also published as: WO2020133257A1; CN112654857B

Abstract

A method of correcting a parameter of a measurement object, a blood cell analyzer (400) and a storage medium, the method of correcting the parameter of the measurement object being used for the blood cell analyzer, the method of correcting the parameter of the measurement object including: acquiring type information (101) of a measurement object; acquiring a detection value (102) of a measurement object; a detection value of the measurement object is processed (103) based on the type information of the measurement object.

Description

Method for processing detection value of measurement object, blood cell analyzer, and storage medium

Technical Field

The present invention relates to the field of blood analysis, and in particular, to a method of processing a detection value of a measurement target, a blood cell analyzer, and a storage medium.

Background

In general, a blood cell analyzer includes a control substance and a calibrator in addition to fresh blood. The quality control substance is a substance with known content and definite characteristics in the same matrix as an actual sample in clinical medical examination, and plays an important role in quality control of a laboratory as the substance for checking the accuracy of an analysis process or an instrument in routine work. The calibrator is used for ensuring accurate and reliable detection results of the hematology analyzer, and has traceability, and the calibrator recommended by a manufacturer or the fixed-value fresh blood provided by a calibration laboratory are required to be used in the calibration guideline for the hematology analysis. However, the quality control and calibration substances, although being mimics of fresh blood, still differ in particle properties.

Furthermore, the reliability of medical test results directly affects the medical quality, wherein temperature is an important factor affecting test results. For example, the normal operating temperature of a hematology analyzer is generally in the range of 18-25 degrees celsius, but due to practical conditions, the hematology analyzer may not operate in the normal temperature range, thereby affecting the test results. In order to solve the adverse effect of temperature on volume measurement, a temperature control system is currently adopted. However, the temperature control system will increase the cost, and will increase the extra time to keep the dilution constant, and decrease the measurement speed.

Disclosure of Invention

In order to solve the above technical problems, embodiments of the present application desirably provide a method for processing a detection value of a measurement object, a blood cell analyzer, and a storage medium, which can simply improve accuracy of a detection result of the blood analyzer on different types of test samples, and in particular, can simply reduce an influence of temperature on the detection result of the blood cell analyzer, so as to avoid an accuracy of quality control or a calibration process of the blood analyzer from being impaired or even failing.

A first aspect of the present application relates to a method of correcting a parameter of a measurement object, the method comprising:

acquiring type information of a measurement object;

acquiring a detection value of the measurement object;

and processing the detection value of the measurement object according to the type information of the measurement object.

In some embodiments of the present application, the type information of the measurement object includes a blood sample, a quality control substance, or a calibration substance.

In some embodiments of the present application, the step of obtaining the type information of the measurement object may include:

acquiring at least two optical signals of a forward scattered light signal, a side scattered light signal and a fluorescent signal of a particle in the measurement object;

forming a measurement object scattergram according to the at least two optical signals;

and comparing the measurement object scatter diagram with a preset scatter diagram to determine the type information of the measurement object.

Alternatively, in some embodiments of the present application, the step of obtaining the type information of the measurement object may also include:

and acquiring the type information of the measuring object according to a preset measuring mode.

In some embodiments of the present application, the step of acquiring a detection value of the measurement object may include:

and accordingly

The step of processing the detection value of the measurement object according to the type information of the measurement object includes:

the at least two optical signals are processed according to a classification algorithm related to the type information of the measurement object to classify and count particles in the measurement object and/or the at least two optical signals, in particular fluorescence signals, are gain amplified according to the type information of the measurement object.

In some embodiments of the method of the present application, before the step of processing the at least two light signals according to a classification algorithm related to the type information of the measurement object, the method may further include:

and acquiring the classification algorithm from a pre-stored classification algorithm database or through RFID or the Internet according to the type information of the measured object.

Further, in some embodiments of the method of the present application, the step of acquiring a detection value of the measurement object may further include:

acquiring volume distribution information of a measurement object suspended in a diluent and the temperature of the diluent;

and in response thereto,

and correcting the volume distribution information of the measuring object by using a temperature correction algorithm related to the type information of the measuring object according to the temperature of the diluent.

In some embodiments of the method of the present application, before the step of correcting the volume distribution information of the measurement object by using a temperature correction algorithm related to the type information of the measurement object according to the temperature of the diluent, the method may further include:

and acquiring the temperature correction algorithm from a pre-stored temperature correction algorithm database or through RFID or the Internet according to the type information of the measurement object.

In some embodiments of the present application, the temperature correction algorithm may be a temperature correction curve; the temperature correction curve may be a fitted curve, particularly a piecewise fitted curve, of the volume distribution information of the measurement object with respect to the temperature, and may be, for example, a first-order fitted curve or a second-order fitted curve, particularly a piecewise linear function.

In some embodiments of the methods of the present application, the temperature correction algorithm corresponding to the blood sample is a negative correlation function of the volume distribution information of the blood sample and the temperature, and the temperature correction algorithm corresponding to the quality control substance or the calibration substance is a positive correlation function of the volume distribution information of the quality control substance or the calibration substance and the temperature.

In some embodiments of the methods of the present application, the method may further comprise:

acquiring the batch of the diluent, and determining the temperature correction algorithm according to the type information of the measurement object and the batch of the diluent.

In some embodiments of the methods of the present application, the volume distribution information may include mean cell volume and cell distribution width standard deviation.

and calculating other parameter information of the measuring object related to the volume distribution information according to the corrected volume distribution information.

outputting the volume distribution information before correction, the volume distribution information after correction and the other parameter information;

optionally also outputting the temperature correction algorithm.

Preferably, the method may further include marking the modified volume distribution information and the other parameter information.

A second aspect of the present application relates to a blood cell analyzer, wherein the blood cell analyzer includes:

a sampling device configured to suck a measurement object;

the pretreatment device is used for pretreating the measurement object so as to obtain a pretreated measurement object;

the detection device is used for detecting the preprocessed measurement object;

a processor configured to perform the steps of:

acquiring type information of the measuring object;

acquiring a detection value of the measurement object;

In some embodiments of the blood cell analyzer of the present application, the type information of the measurement object may include a blood sample, a quality control substance, or a calibration substance.

In some embodiments of the blood cell analyzer of the present application, the processor is configured to, when performing the step of acquiring the type information of the measurement object, perform the following steps:

comparing the measurement object scatter diagram with a preset scatter diagram to determine the type information of the measurement object;

alternatively, the first and second electrodes may be,

the processor is configured to further obtain type information of the measurement object according to a preset measurement mode when the step of obtaining the type information of the measurement object is performed.

In some embodiments of the hematology analyzer of the present application, the processor may be configured to: acquiring at least two optical signals of a forward scattered light signal, a side scattered light signal, and a fluorescent signal of a particle in the measurement object when the step of acquiring a detection value of the measurement object is performed; and in performing the step of processing the detection value of the measurement object according to the type information of the measurement object, the at least two optical signals are processed according to a classification algorithm related to the type information of the measurement object to classify and count particles in the measurement object, and/or the at least two optical signals, particularly fluorescence signals, are gain-amplified according to the type information of the measurement object.

In some embodiments of the blood cell analyzer of the present application, the processor may be further configured to obtain the classification algorithm from a pre-stored classification algorithm database or through RFID or the internet according to the type information of the measurement object before processing the at least two optical signals according to the classification algorithm associated with the type information of the measurement object.

In some embodiments of the blood cell analyzer of the present application, the blood cell analyzer may further include a sensing device configured to detect a temperature of a diluent in which the measurement object is located; and

the processor may be configured to: acquiring volume distribution information of the measurement object suspended in the diluent and a temperature of the diluent when the step of acquiring the measurement value of the measurement object is performed; and correcting the volume distribution information by using a temperature correction algorithm associated with the type information of the measurement object, based on the temperature of the diluent, when the step of processing the detection value of the measurement object based on the type information of the measurement object is performed.

In some embodiments of the blood cell analyzer of the present application, the processor may be configured to obtain the temperature correction algorithm from a pre-stored temperature correction algorithm database or through RFID or internet according to the type information of the measurement object before performing the step of correcting the volume distribution information using a temperature correction algorithm associated with the type information of the measurement object according to the temperature of the diluent.

In some embodiments of the blood cell analyzer of the present application, the temperature correction algorithm may be a temperature correction curve which is a fitted curve, in particular a piecewise fitted curve, of the volume distribution information of the measurement object with respect to temperature, for example, may be a first-order fitted curve or a second-order fitted curve, in particular a piecewise linear function.

In some embodiments of the hematology analyzer of the present application, the temperature correction algorithm corresponding to the blood sample is a negative correlation function of the volume distribution information of the blood sample and the temperature, and the temperature correction algorithm corresponding to the control or calibration material is a positive correlation function of the volume distribution information of the control or calibration material and the temperature.

In some embodiments of the blood cell analyzer of the present application, the processor may be further configured to calculate other parameter information of the measurement object related to the volume distribution information according to the corrected volume distribution information.

In some embodiments of the present application, the processor may be further configured to output the volume distribution information before the correction, the volume distribution information after the correction, and the other parameter information and optionally output the temperature correction curve; and marking the corrected volume distribution information and the other parameter information.

A third aspect of the present application relates to a computer-readable storage medium having stored thereon a program which, when executed by a processor, carries out the steps of the above-described method of processing a parameter of a measurement object of the first aspect of the present application.

According to the method and the blood cell analyzer, the detection value of the blood cell analyzer is processed by adopting the processing algorithm related to the type of the measurement object, so that the accuracy of the detection result of the blood analyzer on different types of test samples can be simply improved, particularly, the influence of temperature on the detection result of the blood cell analyzer can be simply reduced, and the quality control of the blood analyzer or the accuracy of the calibration process can be prevented from being damaged or even losing efficacy.

Drawings

Fig. 1 is a first schematic flowchart of a method for processing a detection value of a measurement object according to an embodiment of the present application;

fig. 2 is a schematic flowchart of a method for processing a detection value of a measurement object according to an embodiment of the present application;

fig. 3A to 3C are comparative diagrams of scattergrams of different measurement objects and a reference scattergram;

FIG. 4A is a fluorescence-forward scattering scattergram of a quality control substance;

FIG. 4B is a fluorescence-forward scattered light scattergram of a blood sample;

FIG. 4C is a fluorescence-forward scattered light scattergram of the quality control after amplification of the fluorescence signal of the quality control;

FIG. 5A is a fluorescence-forward scattering scattergram of a control substance with a cluster marked off;

FIG. 5B is a fluorescence-forward scattered light scattergram of a blood sample demarcated into clusters;

FIG. 6A is a graph showing the relative deviation of MCV in a control substance with temperature;

FIG. 6B is a graph showing the relative variation of the RDW-SD of the red blood cells in the quality control substance with the temperature;

FIG. 7A is a graph showing the relative deviation of red blood cell MCV in a calibrator as a function of temperature;

FIG. 7B is a graph showing the relative deviation of red blood cell RDW-SD in the calibrant as a function of temperature;

FIG. 8A is a graph showing the relative deviation of red blood cell MCV in a blood sample as a function of temperature;

FIG. 8B is a graph showing the relative deviation of red blood cell RDW-SD in a blood sample as a function of temperature;

FIG. 9A is a diagram showing the absolute deviation of MCV in a controlled substance with temperature and a first-fit temperature correction curve according to an embodiment of the present disclosure;

FIG. 9B is a graph showing the relative deviation of MCV in the control before and after temperature correction using the first-fit curve shown in FIG. 9A;

FIG. 9C is a diagram showing the absolute deviation of the RDW-SD of the red blood cells in the quality control material with the temperature variation and the corresponding first-fit temperature correction curve according to the embodiment of the present application;

FIG. 9D is a graph showing the relative deviation of red blood cells RDW-SD in the quality control material before and after temperature correction using the first-order fit curve shown in FIG. 9C;

FIG. 10A is a graph showing the absolute deviation of the MCV of red blood cells in a calibrator as a function of temperature and a first-fit temperature correction curve according to an embodiment of the present application;

FIG. 10B is a graph of the relative deviation of red blood cell MCV in a calibrator before and after temperature correction using the first-fit curve shown in FIG. 10A;

FIG. 10C is a graph showing the absolute deviation of RDW-SD of red blood cells in a calibrator as a function of temperature and a first-fit temperature correction curve according to an embodiment of the present application;

FIG. 10D is a graph showing the relative deviation of red blood cell RDW-SD in the calibrator before and after temperature correction using the first-fit curve shown in FIG. 10C;

FIG. 11A is a graph showing the absolute deviation of MCV in a blood sample as a function of temperature and a first-fit temperature correction curve according to an embodiment of the present application;

FIG. 11B is a graph showing the relative deviation of red blood cell MCV in a blood sample before and after temperature correction using the first-fit curve shown in FIG. 11A;

FIG. 11C is a graph showing the absolute deviation of RDW-SD of red blood cells in a blood sample as a function of temperature and a first-fit temperature correction curve according to an embodiment of the present application;

FIG. 11D is a graph of the relative deviation of red blood cell RDW-SD in a blood sample before and after temperature correction using the first-fit curve shown in FIG. 11C;

FIG. 12A is a diagram showing the absolute deviation of MCV in a controlled substance with temperature and the corresponding quadratic temperature correction curve according to the embodiment of the present application;

FIG. 12B is a graph showing the relative deviation of MCV in the control before and after temperature correction using the quadratic fit curve shown in FIG. 12A;

FIG. 12C is a diagram showing the absolute deviation of the RDW-SD of the red blood cells in the quality control material with the temperature variation and the corresponding quadratic fitting temperature correction curve according to the embodiment of the present application;

FIG. 12D is a graph showing the relative deviation of red blood cells RDW-SD in the quality control material before and after temperature correction using the quadratic fit curve shown in FIG. 12C;

FIG. 13A is a graph showing the absolute deviation of red blood cell MCV in a calibrator as a function of temperature and a quadratic temperature correction curve according to an embodiment of the present application;

FIG. 13B is a graph of the relative deviation of red blood cell MCV in a calibrator before and after temperature correction using the quadratic fit curve shown in FIG. 13A;

FIG. 13C is a graph showing the absolute deviation of RDW-SD of red blood cells in a calibrator as a function of temperature and the corresponding quadratic temperature correction curve proposed in the examples herein;

FIG. 13D is a graph of the relative deviation of red blood cell RDW-SD in the calibrant before and after temperature correction using the quadratic fit curve shown in FIG. 13C;

FIG. 14A is a graph showing the absolute deviation of MCV in a blood sample as a function of temperature and a corresponding quadratic temperature correction curve according to an embodiment of the present application;

FIG. 14B is a graph of the relative deviation of red blood cell MCV in a blood sample before and after temperature correction using the quadratic fit curve shown in FIG. 14A;

FIG. 14C is a graph showing the absolute deviation of RDW-SD of red blood cells in a blood sample as a function of temperature and the corresponding quadratic temperature correction curve proposed in the embodiments of the present application;

FIG. 14D is a graph of the relative deviation of red blood cell RDW-SD in a blood sample before and after temperature correction using the quadratic fit curve shown in FIG. 14D;

fig. 15 is a third schematic flowchart of a method for processing a detection value of a measurement object according to an embodiment of the present application;

fig. 16 is a fourth schematic flowchart of a method for processing a detection value of a measurement object according to an embodiment of the present application.

Fig. 17 is a schematic structural diagram of a blood cell analyzer according to an embodiment of the present application.

Detailed Description

In order to understand the features and technical contents of the embodiments of the present application more thoroughly, the technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant application and are not limiting of the application. It should be noted that, for the convenience of description, only the parts related to the related applications are shown in the drawings.

An embodiment of the present application provides a method of processing a measurement value of a measurement object, particularly for use in a blood cell analyzer. Fig. 1 is a schematic flow diagram one of a method according to the present application. As shown in fig. 1, the method comprises the steps of:

step 101, obtaining type information of a measurement object.

In the embodiments of the present application, the measurement object may be a blood sample, a quality control substance, or a calibrator. Although the quality control substance or the calibration substance is a simulation of the blood sample, the properties of the quality control substance or the calibration substance are not completely the same in terms of particles, and for example, different temperatures affect the measurement of the cell volume of the blood sample, the quality control substance, and the calibration substance to different degrees, so that it is necessary to acquire type information of the measurement object in advance when analyzing a detection value of the measurement object.

As shown in fig. 2, which is a schematic flow chart of a method according to the present application, in an embodiment of the present application, the step 101 of acquiring the type information of the measurement object may include the following steps:

101a, acquiring at least two optical signals of forward scattered light signals, side scattered light signals and fluorescence signals of the measuring object which is processed by the hemolytic agent and the fluorescent dye.

101b, forming a measurement object scatter diagram according to at least two kinds of optical signals.

And 101c, comparing the scatter diagram of the measurement object with a preset scatter diagram to determine the type information of the measurement object.

Specifically, the preset scattergram may include at least two of a quality control scattergram, a calibrant scattergram, and a blood scattergram. For example, when the preset scattergram includes a quality control object scattergram and a calibrator scattergram, if the scattergram of the measurement object is similar to the quality control object scattergram or the calibrator, the measurement object is determined to be the quality control object or the calibrator, otherwise, the measurement object is determined to be the blood sample. Referring to fig. 3A to 3C, fig. 3A to 3C are comparison diagrams of a scattergram of different measurement objects and a reference scattergram, wherein fig. 3A is a comparison diagram of a scattergram when the measurement object is a quality control object and a preset scattergram, that is, a reference scattergram; fig. 3B is a comparison graph of a scattergram when the measurement object is the calibration object and a preset scattergram, that is, a reference scattergram; fig. 3C is a comparison graph of the scattergram when the measurement target is a blood sample and a reference scattergram which is a preset scattergram. The similarity between the measurement object scatter diagram and the predetermined scatter diagram may be difference between the scatter diagrams/correlation coefficient/mutual information/edge envelope information of the scatter diagram. Since the blood sample has various scattergram forms and the quality control substance and the calibrator are relatively stable, the preset scattergram preferably includes a quality control substance scattergram and a calibrator scattergram.

Furthermore, in an alternative embodiment, the type information of the measurement object may also be obtained by setting different measurement modes. The measurement mode may be a blood measurement mode or a control \ calibrator measurement mode. For example, in the embodiment of the present application, before the analysis and detection are performed on the measurement object, the measurement mode is set, and thus the type information of the measurement object is directly determined.

Step 102, a detection value of the measurement object is acquired.

Specifically, in the practice of the present application, the detection value may include at least two of a forward scattered light signal, a side scattered light signal, and a fluorescence signal of the particle in the measurement object subjected to the hemolytic agent treatment and the fluorescent dye treatment. In this case, before the at least two kinds of optical signals are acquired, the particles in the measurement object are first subjected to a pretreatment such as a hemolysis treatment and a fluorescent staining treatment. Specifically, the measurement object is mixed with a reagent having a fluorescent dye and a hemolytic agent in a certain ratio to form a processed measurement object. For example, a hemolytic agent is used to lyse red blood cells in a measurement object so as not to interfere with counting of particles such as white blood cells, and a fluorescent dye is bound to nucleic acid of white blood cells to label the cells, and different fluorescent information is generated due to differences in the ability of each type of cell to bind the fluorescent dye. In addition, different forward scattering light information can be generated due to different sizes of various cells, and different side scattering light information can be generated due to different shapes or complexity in the cells.

The detection value may include volume distribution information of particles in the measurement object, particularly volume distribution information of red blood cell particles, and a temperature of the diluent in which the measurement object is located. For example, the measurement object in the diluent is detected by an electrical impedance method, thereby obtaining information on the volume distribution of the red blood cell particles of the measurement object suspended in the diluent.

The volume distribution information may include a mean cell volume and a cell distribution width standard deviation. Specifically, the Volume Distribution information may be Mean Corpuscular Volume (MCV) and Red Blood Cell Distribution Width Standard Deviation (RDW-SD).

Further, in the embodiment of the present application, since there is a significant difference between cells measured according to the coulter principle at different temperatures, the temperature of the diluent has a large influence on the accuracy of the detection result, and therefore, when the blood cell analyzer performs analysis detection on a measurement object suspended in the diluent, the temperature of the diluent needs to be detected so as to determine how to process the volume distribution parameters of the particles in the measurement object according to the temperature of the diluent.

Step 103, processing the detection value of the measurement object according to the type information of the measurement object.

In an embodiment of the present application, if the detection value includes at least two of a forward scattered light signal, a side scattered light signal, and a fluorescence signal of the particle in the measurement object subjected to the hemolytic agent treatment and the fluorescent dye treatment, step 103 may include: the at least two optical signals are processed according to a classification algorithm related to the type information of the measurement object to classify and count particles in the measurement object, and/or the at least two optical signals, in particular the fluorescence signals, are gain amplified according to the type information of the measurement object.

On the other hand, as shown in fig. 4A and 4B, fig. 4A is a fluorescence-forward scattered light scattergram of a quality control substance, and fig. 4B is a fluorescence-forward scattered light scattergram of a blood sample, and since particles in the quality control substance or a calibrator are fixed by a reagent, the ability to absorb a fluorescent substance is weak, and a signal of the quality control substance or the calibrator in a fluorescence direction is smaller than that of the blood sample, so that there is a difference in the position of a particle mass on the scattergram consisting of fluorescence-forward scattered light signals. By appropriately amplifying the signal of the quality control substance or the calibrator in the fluorescence direction, the position of the particle mass in the quality control substance or the calibrator in the fluorescence-forward scattered light scattergram can be made substantially similar to that of the blood sample, thereby better classifying the particles in different types of measurement objects, as shown in fig. 4C, which is the fluorescence-forward scattered light scattergram of the quality control substance after 80% amplification of the fluorescence signal of the quality control substance.

On the other hand, as shown in fig. 5A and 5B, fig. 5A is a fluorescence-forward scattering scattergram of a divided particle group of a quality control substance, and fig. 5B is a fluorescence-forward scattering scattergram of a divided particle group of a blood sample, and BASO particles (BASO particles) in the quality control substance are different from BASO particles in the blood sample due to a process at the time of preparing the quality control substance, so that the BASO particles in the quality control substance are different from the BASO particles in the blood sample in position in the fluorescence-forward scattering scattergram. Therefore, it is necessary to process the optical signals of the particles in the measurement object using a classification algorithm related to the type information of the measurement object to accurately classify and count the particles in the measurement object. That is, different classification algorithms are employed for different types of measurement objects.

Further, in the embodiment of the present application, before the step of processing the at least two optical signals according to the classification algorithm related to the type information of the measurement object, the classification algorithm related to the type information of the measurement object may be acquired. Specifically, the above blood cell analyzer may acquire the classification algorithm from a pre-stored classification algorithm database or through Radio Frequency Identification (RFID) or the internet according to the type information of the measurement object.

In an embodiment of the present application, if the above-mentioned detection values further include volume distribution information of particles of the measurement object suspended in the diluent, for example, red blood cell particles, and a temperature of the diluent, step 103 may further include: and correcting the volume distribution information by using a temperature correction algorithm related to the type information of the measurement object according to the temperature of the diluent.

At present, the majority of micropore impedance principles are used for the measurement of blood cells, such as red blood cells, by medical particle analyzers, such as blood cell analyzers, which are based on the coulter principle. The specific detection process comprises the following steps: particles suspended in the electrolyte pass through the detection micropores along with the electrolyte, namely diluent, the equivalent resistance at the detection micropores can change, the voltage at two sides of the detection micropores changes under the action of constant current sources at two sides of the micropores, and the voltage change is collected through a circuit system to form a voltage pulse waveform. The height of the pulse waveform reflects the volume size of the cell, and represents the volume information of the particle, so that the instrument provides the volume distribution of the detected particle accordingly, i.e. provides a volume distribution histogram of the detected particle. And analyzing the cell volume histogram, namely classifying and counting the cells. This measurement method is also called electrical impedance method.

Through a large amount of research and clinical experiments, the applicant finds that the cells obtained by measurement according to the Coulter principle at different temperatures have obvious difference. Also, the degree of temperature effect on fresh blood and control or calibrator cell volume measurements is not the same. On the one hand, this affects the accuracy of normal blood sample measurement, and on the other hand, it also results in the accuracy of quality control or calibration procedures being impaired or even disabled, for example, the temperature rise results in the volume of quality control object detection being reduced and out of the quality control range, but the actual instrument has no problem, and actually is false positive.

In an embodiment of the present invention, the blood cell analyzer may be configured to obtain volume distribution information of particles to be measured in a diluent, a temperature of the diluent, and type information of the particles to be measured, and then correct the volume distribution information of the particles to be measured by using a temperature correction algorithm associated with the type information of the particles to be measured based on the temperature of the diluent. Specifically, after acquiring the type information of the measurement object, a temperature correction algorithm corresponding to the type information of the measurement object may be acquired.

In this embodiment, by correcting the volume distribution information of the measurement object by using the temperature correction algorithm related to the type information of the measurement object according to the temperature of the diluent, the influence of the temperature on the detection results of different measurement objects can be eliminated in a simple manner, so that the accuracy of the detection result of the blood sample can be improved and the accuracy of the quality control or calibration process can be prevented from being damaged or even failing.

In the embodiment of the present application, the temperature correction algorithm corresponding to the type information of the measurement target may be a temperature correction curve corresponding to the type information of the measurement target.

Specifically, when the volume distribution information of the measurement target is corrected by a temperature correction algorithm relating to the type information of the measurement target based on the temperature of the diluent, the blood cell analyzer may determine a temperature correction parameter corresponding to the temperature of the diluent from the temperature correction algorithm and then correct the volume distribution information based on the temperature correction parameter.

Since the influence of temperature on the detection results of different types of measurement objects is different, the detection results of the measurement objects should be corrected using a temperature correction curve relating to the type information of the measurement objects.

Further, in the embodiment of the present application, when the type of the measurement object is a quality control object/calibration object, the corresponding temperature correction algorithm, especially the temperature correction curve, is in positive correlation with the temperature change; when the type of the measurement object is a blood sample, the corresponding temperature correction algorithm, especially the temperature correction curve, is inversely related to the temperature change. That is, the temperature correction algorithm, particularly the temperature correction curve, corresponding to the blood sample is a negative correlation function of the volume distribution information of the blood sample and the temperature; the temperature correction algorithm, particularly the temperature correction curve, corresponding to the mass control substance/calibrator is a positive correlation function of the volume distribution information of the mass control substance/calibrator and the temperature.

See in particular fig. 6 to 8. Fig. 6A is a schematic diagram of the relative deviation of the red blood cell MCV in the quality control substance with the temperature change, and fig. 6B is a schematic diagram of the relative deviation of the red blood cell RDW-SD in the quality control substance with the temperature change, so that it can be seen that the red blood cell MCV and RDW-SD in the quality control substance both decrease with the temperature increase, and thus, the temperature correction curve corresponding to the quality control substance should be positively correlated with the temperature change. FIG. 7A is a graph showing the relative deviation of the MCV of the red blood cells in the calibrator as a function of temperature, and FIG. 7B is a graph showing the relative deviation of the RDW-SD of the red blood cells in the calibrator as a function of temperature. Fig. 8A is a graph showing the relative deviation of the MCV of the red blood cells in the blood sample according to the temperature change, and fig. 8B is a graph showing the relative deviation of the RDW-SD of the red blood cells in the blood sample according to the temperature change, wherein the MCV and RDW-SD of the red blood cells in the blood sample increase with the temperature increase, so that the temperature correction curve corresponding to the blood sample should be in positive and negative correlation with the temperature change.

It should be noted here that the "deviation" in the present application is based on a temperature of 22 ℃. Those skilled in the art can use different reference standards to obtain the corresponding deviation value according to actual situations.

In addition, it should be noted that, in the embodiment of the present application, for different batches of diluents, corresponding temperature correction algorithms, especially temperature correction curves, are also different, so that when the blood cell analyzer acquires the temperature correction algorithms, identification information corresponding to the diluents may be acquired first; wherein the identification information is used to determine the batch of diluent; and then determining the temperature correction algorithm according to the type information of the measuring object and the batch of the diluent.

Further, in an embodiment of the present invention, the blood cell analyzer may acquire the temperature correction algorithm before correcting the volume distribution information of the measurement target by using the temperature correction algorithm related to the type information of the measurement target according to the temperature of the diluent. Specifically, the above-described slave blood cell analyzer may acquire the temperature correction algorithm from a pre-stored temperature correction algorithm database or through RFID or the internet according to the type information of the measurement object.

It should be noted that, in the embodiment of the present application, the temperature correction curve may be a fitted curve of the volume distribution information of the measurement object with respect to the temperature, in particular, a piecewise fitted curve, for example, a first-order fitted curve or a second-order fitted curve, in particular, a piecewise linear function.

Further, in the embodiment of the present application, when the blood cell analyzer performs the temperature correction, the type of the measurement object, the type of the volume distribution information, and the temperature correction curve are in one-to-one correspondence, that is, there is one corresponding temperature correction curve for one measurement object and one volume distribution information of the measurement object.

An embodiment of correcting volume distribution information of particles to be measured, particularly red blood cell particles, using a first-order fit curve, i.e., a straight line, will now be described with reference to fig. 9 to 11. Fig. 9A is a schematic diagram of the absolute deviation of the red blood cell MCV in the control substance with the temperature change and the corresponding first-fit temperature correction curve, wherein y is 0.2785t-6.4055, and after the temperature correction, the relative deviation of the control substance MCV before and after the temperature correction is as shown in fig. 9B; fig. 9C is a schematic diagram of the absolute deviation of the red blood cells RDW-SD in the control substance according to the temperature change and the corresponding first-fit temperature correction curve, wherein the first-fit temperature correction curve is y-0.0811 t-1.8653, and fig. 9D is a schematic diagram of the relative deviation of the red blood cells RDW-SD in the control substance before and after the temperature correction by using the first-fit curve shown in fig. 9C. Similarly, fig. 10A is a schematic diagram of the absolute deviation of the red blood cell MCV in the calibrator with respect to the change in temperature and a corresponding first-fit temperature correction curve, where y is 0.2761t-6.35, and fig. 10B is a schematic diagram of the relative deviation of the red blood cell MCV in the calibrator before and after the temperature correction using the first-fit curve shown in fig. 10A; fig. 10C is a graph showing the absolute deviation of the red blood cell RDW-SD in the calibrator as a function of temperature and the corresponding first-fit temperature correction curve, where y is 0.1032t-2.3736, and fig. 10D is a graph showing the relative deviation of the red blood cell RDW-SD in the calibrator before and after temperature correction using the first-fit curve shown in fig. 10C. Finally, fig. 11A is a schematic diagram of the absolute deviation of the MCV of the erythrocytes in the blood sample according to the temperature variation and the corresponding first-fit temperature correction curve, wherein the first-fit temperature correction curve is y-0.3648 t +8.0256, and fig. 11B is a schematic diagram of the relative deviation of the MCV of the erythrocytes in the blood sample before and after the temperature correction by using the first-fit curve shown in fig. 11A; fig. 11C is a graph showing the absolute deviation of RDW-SD of erythrocytes in blood samples according to the temperature variation and the corresponding first-fit temperature correction curve, wherein y is-0.2117 t +4.6574, and fig. 11D is a graph showing the relative deviation of RDW-SD of erythrocytes in blood samples before and after temperature correction using the first-fit curve shown in fig. 11C.

Next, an embodiment of correcting volume distribution information of particles to be measured, particularly red blood cell particles, using a quadratic fit curve will be described with reference to fig. 12 to 14. FIG. 12A is a diagram of the absolute deviation of the MCV of the red blood cells in the quality control material with the temperature variation and the corresponding quadratic fitting temperature correction curve, wherein the quadratic fitting temperature correction curve is y-0.0048 t²+0.5006 × t-9.0381, fig. 12B is a schematic representation of the relative deviation of red blood cells MCV in the control before and after temperature correction using the quadratic fit curve shown in fig. 12A; FIG. 12C is a diagram of the absolute deviation of red blood cells RDW-SD in the quality control material with the temperature variation and the corresponding quadratic fitting temperature correction curve, wherein the quadratic fitting temperature correction curve is y-0.0018 t²+0.163 × t-2.7708, and fig. 12D is a graph showing the relative deviation of red blood cells RDW-SD in the control before and after temperature correction using the quadratic fit curve shown in fig. 12C. Similarly, fig. 13A is a schematic diagram of the absolute deviation of the MCV of the erythrocytes in the calibrator with the change of temperature and the corresponding quadratic temperature correction curve, wherein the quadratic temperature correction curve is y-0.0078 × t²+0.6373 × t-10.518, and fig. 13B is a graph of the relative deviation of red blood cell MCV in the calibrant before and after temperature correction using the quadratic fit curve shown in fig. 13A; fig. 13C is a graph of the absolute deviation of red blood cell RDW-SD in the calibrant as a function of temperature and the corresponding quadratic temperature correction curve, where y is-0.0019 × t²+0.1896 × t-3.3836, and fig. 13D is a graph of relative deviation of red blood cell RDW-SD in calibrators before and after temperature correction using a quadratic fit curve. Finally, fig. 14A is a schematic diagram of the absolute deviation of the MCV of the red blood cells in the blood sample with the temperature variation and the corresponding quadratic fitting temperature correction curve, wherein the quadratic fitting temperature correction curve is y-0.0004 × t²-0.3821 × t +8.3162, and fig. 14B is a graph of the relative deviation of red blood cell MCV in a blood sample before and after temperature correction using the quadratic fit curve shown in fig. 14A; fig. 14C is a schematic diagram of the absolute deviation of red blood cell RDW-SD in blood samples as a function of temperature and the corresponding quadratic temperature correction curve, where y is 0.0016 × t²-0.2838 × t +5.5721, and fig. 14D is a graph of relative deviation of red blood cells RDW-SD in a blood sample before and after temperature correction using the quadratic fit curve shown in fig. 14C.

Therefore, after the blood cell analyzer performs temperature correction according to the temperature correction curve, more accurate measurement results can be obtained for the volume distribution information of the particles of the quality control substance, the calibrator and the blood sample.

Fig. 15 is a third schematic flowchart of a method for processing a detection value of a measurement object according to an embodiment of the present application. In the embodiment shown in fig. 15, the method comprises the steps of:

step 201, obtaining type information of a measurement object;

step 202, obtaining volume distribution parameters of particles of a measurement object suspended in a diluent and the temperature of the diluent;

step 203, judging whether the temperature of the diluent falls into a preset temperature range;

when the temperature of the diluent falls within the preset temperature range, step 203b is performed, i.e., no temperature correction is performed;

when the diluent temperature is not within the preset temperature range, step 203a is performed, in which the volume distribution information is corrected using a temperature correction algorithm associated with the type information of the measurement object according to the diluent temperature.

In this embodiment of the present application, since temperature correction is not required for the detection result under the experimental condition that the temperature of the diluent is appropriate, the temperature of the diluent may also be used to determine whether to start the temperature correction function. Specifically, the blood cell analyzer may determine whether the temperature of the diluent falls within a preset temperature range after acquiring the temperature of the diluent, and if so, turn off the temperature correction function, otherwise, perform temperature correction. The preset temperature range is used to represent a normal operating temperature range of the hematology analyzer, and for example, the preset temperature range may be 18-25 ℃.

Fig. 16 is a fourth schematic flowchart of a method for processing a detection value of a measurement object according to an embodiment of the present application. In this embodiment, steps 301 to 303 are the same as steps 201 to 203, respectively, of the embodiment shown in fig. 15, except that: the method further comprises, after step 303: step 304, calculating other parameter information of the measuring object related to the volume distribution information according to the corrected volume distribution information; and step 305, outputting the volume distribution information before correction, the volume distribution information after correction and other parameter information, and preferably, also outputting the temperature correction algorithm.

Therefore, in this embodiment of the present application, the blood cell analyzer displays the volume distribution parameter before correction and the volume distribution parameter after correction, and optionally displays other parameter information and a temperature correction curve related to the volume distribution information, after performing temperature correction on the volume distribution parameter of the measurement object according to the temperature of the diluent and the temperature correction curve, so as to help the medical staff perform comparison and analysis more intuitively.

Specifically, the hemocyte analyzer can calculate, for example, relative parameters such as Hematocrit (HCT), Mean Corpuscular Hemoglobin (MCH), and Mean Corpuscular Hemoglobin Concentration (MCHC) from the corrected erythrocytes MCV and RDW-SD.

In the embodiment of the present invention, after calculating other parameter information related to the volume distribution information of the measurement target based on the corrected volume distribution information, the blood cell analyzer may output the volume distribution information before correction, the temperature correction algorithm, the corrected volume distribution information, and the other parameter information, and may mark the corrected volume distribution information and the other parameter information.

As shown in fig. 17, the present application also provides a blood cell analyzer 400, the blood cell analyzer 400 including: a sampling device (not shown) arranged to aspirate the test object; a preprocessing device 410 configured to perform preprocessing on the measurement object so as to obtain a preprocessed measurement object, where the preprocessing may include, for example, performing hemolysis processing and fluorescence staining processing on particles in the measurement object; a detection device 420 configured to detect the preprocessed measurement object; and a processor 430 for performing the above method.

The detection device 420 may include, but is not limited to, a light source 421 and a sheath flow chamber 422 having an aperture, and the particles in the blood sample may flow in the sheath flow chamber 422 and pass through the aperture one by one. Light emitted by the light source 421 can strike the particles in the aperture and correspondingly produce a scattered light signal and/or a fluorescent signal. The optical detection device 420 may further include a flow cell 422 as a detection region, a forward scattered light collection portion 423 disposed on the optical axis, a side scattered light collection device portion 424 and a fluorescence collection portion 425 disposed on the side of the optical axis. The particles of the measurement object processed by the preprocessing device 410 sequentially enter the flow chamber 422 (detection region) through the pipe 440, wherein the forward scattered light collecting part 423, the side scattered light collecting device part 424, and the fluorescence collecting part 425 in the same channel sequentially detect and collect forward scattered light information, side scattered light information, and fluorescence information of each cell, and transmit to the processor 430.

The processor 430 may be implemented in a host and perform the following method steps:

acquiring type information of the measuring object;

acquiring a detection value of the measurement object;

Further, in an embodiment of the present application, the type information of the measurement object includes a blood sample, a quality control substance, or a calibration substance.

Further, in an embodiment of the present application, the processor 530 is specifically configured to, when the step of obtaining the type information of the measurement object is performed, perform the following steps:

acquiring at least two optical signals of a forward scattered light signal, a side scattered light signal and a fluorescent signal of the measuring object which is processed by a hemolytic agent and a fluorescent dye;

In an alternative embodiment of the present application, the processor 530 may be specifically configured to obtain the type information of the measurement object according to a preset measurement mode when the step of obtaining the type information of the measurement object is performed.

Further, in an embodiment of the present application, the processor is configured to: acquiring at least two of forward scattered light signals, side scattered light signals, and fluorescence signals of particles in the measurement object subjected to hemolytic agent treatment and fluorescent dye treatment when the step of acquiring the detection value of the measurement object is performed; and in performing the step of processing the detection value of the measurement object according to the type information of the measurement object, the at least two optical signals are processed according to a classification algorithm related to the type information of the measurement object to classify and count particles in the measurement object, and/or the at least two optical signals, particularly fluorescence signals, are gain-amplified according to the type information of the measurement object.

Further, in the embodiment of the present application, the processor 430 is further configured to obtain the classification algorithm from a pre-stored classification algorithm database or through RFID or the internet according to the type information of the measurement object before processing the at least two optical signals according to the classification algorithm related to the type information of the measurement object.

Further, in an embodiment of the present application, the blood cell analyzer further includes a sensing device configured to detect a temperature of a diluent in which the measurement object is located. At this point, the processor is configured to: acquiring volume distribution information of the measurement object suspended in the diluent and a temperature of the diluent while the step of acquiring the measurement value of the measurement object is performed; and correcting the volume distribution information by using a temperature correction algorithm associated with the type information of the measurement object, based on the temperature of the diluent, when the step of processing the detection value of the measurement object based on the type information of the measurement object is performed.

Further, in the embodiment of the present application, the processor 430 is configured to obtain the temperature correction algorithm from a pre-stored temperature correction algorithm database or through RFID or internet according to the type information of the measurement object before performing the step of correcting the volume distribution information by using the temperature correction algorithm associated with the type information of the measurement object according to the temperature of the diluent.

Further, in the embodiment of the present application, the processor 430 is further configured to determine whether the diluent temperature falls within a preset temperature range before the volume distribution information is corrected by using a temperature correction algorithm associated with the type information of the measurement object according to the diluent temperature, and not perform the correction when the diluent temperature falls within the preset temperature range.

Further, in the embodiment of the present application, the temperature correction algorithm may be a temperature correction curve, and preferably, the temperature correction curve may be a fitted curve of the volume distribution information of the measurement object with respect to the temperature, such as a first-order fitted curve or a second-order fitted curve. Further, the temperature correction curve may also be a piecewise fitting curve, such as a piecewise linear function, of the volume distribution information of the measurement object with respect to the temperature.

Further, in the embodiment of the present application, the correction algorithm corresponding to the blood sample may be a negative correlation function of the volume distribution information of the blood sample and the temperature; the correction algorithm corresponding to the control or calibration material may be a positive correlation function of the volume distribution information of the control or calibration material and the temperature.

Further, in an embodiment of the present application, the volume distribution information may include a mean cell volume and a cell distribution width standard deviation.

Further, in an embodiment of the present application, the processor 430 may be further configured to calculate other parameter information of the measurement object related to the volume distribution information according to the corrected volume distribution information; and outputting the volume distribution information before the correction, the volume distribution information after the correction and other parameter information related to the volume distribution information, optionally outputting the correction curve.

Further, in an embodiment of the present application, the blood cell analyzer 400 comprises a display device (not shown) configured to display the volume distribution information before modification, the volume distribution information after modification, and other parameter information related to the volume distribution information output by the processor, optionally displaying the modification algorithm.

Further, in an embodiment of the present application, wherein the blood cell analyzer 400 comprises a switching device (not shown) arranged to switch the correction on or off. The switching means may be, for example, physical buttons on the blood cell analyzer 400 or may be virtual buttons on a display device.

In an embodiment of the present Application, the Processor 430 may be at least one of an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a ProgRAMmable Logic Device (PLD), a Field ProgRAMmable Gate Array (FPGA), a Central Processing Unit (CPU), a controller, a microcontroller, and a microprocessor. It is understood that the electronic devices for implementing the above processor functions may be other devices, and the embodiments of the present application are not limited in particular.

In addition, each functional module in this embodiment may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware or a form of a software functional module.

The integrated unit, if implemented in the form of a software functional module and not sold or used as a standalone product, may be stored in a computer readable storage medium, and based on such understanding, a part of the technical solution of the present embodiment that essentially contributes to the prior art or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, which includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute all or part of the steps of the method of the present embodiment. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

Furthermore, an embodiment of the present application also provides a computer-readable storage medium on which a program is stored, which, when executed by a processor, implements the method of processing the detection value of the measurement object as described above.

Specifically, the program instructions corresponding to a method of processing a detection value of a measurement object in the present embodiment may be stored on a storage medium such as an optical disc, a hard disc, a usb disk, or the like, and when the program instructions corresponding to a method of processing a detection value of a measurement object in the storage medium are read or executed by an electronic device, the following steps are performed:

acquiring type information of a measurement object;

acquiring a detection value of the measurement object;

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of implementations of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart block or blocks and/or flowchart block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks in the flowchart and/or block diagram block or blocks.

The features mentioned above can be combined with one another as desired, insofar as they are within the scope of the invention. The advantages and features described for the method according to the invention apply in a corresponding manner to the blood cell analyzer according to the invention.

The above description is only for the embodiments of the present invention and is not intended to limit the scope of the present invention, and all equivalent structural changes made by using the contents of the present specification and the drawings or directly/indirectly applied to other related technical fields under the inventive concept of the present invention are included in the scope of the present invention.

Industrial applicability

The embodiment of the application provides a method for processing a detection value of a measurement object, a blood cell analyzer and a storage medium, wherein the blood cell analyzer acquires type information of the measurement object; acquiring a detection value of a measurement object; the detection value of the measurement object is processed according to the type information of the measurement object. It can be seen that, in the embodiment of the present application, the blood cell analyzer can process the detection values thereof by using different processing algorithms for different types of measurement objects. For example, a blood cell analyzer may classify particles in a type of measurement object using different classification algorithms for the measurement object. In addition, when the blood cell analyzer performs detection analysis on a measurement object in a diluent, the blood cell analyzer can simultaneously detect and obtain volume distribution information including particles of the measurement object, a detection value of the diluent temperature and type information of the measurement object, so that the volume distribution information can be corrected by using a temperature correction algorithm related to the type information of the measurement object according to the diluent temperature, that is, different temperature correction algorithms respectively adopted for a calibrator, a quality controller and a blood sample can be used for correction processing to obtain the corrected volume distribution information and other related parameter information, thereby eliminating the influence of temperature on the detection of the volume distribution information of the measurement object, improving the accuracy of the detection result, and avoiding the accuracy of quality control or a calibration process from being damaged or even losing efficacy.

Claims

A method of processing a detection value of a measurement object, the method comprising:

acquiring type information of a measurement object;

acquiring a detection value of the measurement object;

and processing the detection value of the measurement object according to the type information of the measurement object.
The method of claim 1, wherein the type information of the measurement object includes a blood sample, a quality control substance, or a calibration substance.
The method according to claim 1 or 2, wherein the step of acquiring type information of the measurement object includes:

acquiring at least two optical signals of a forward scattered light signal, a side scattered light signal and a fluorescent signal of a particle in the measurement object;

forming a measurement object scattergram according to the at least two optical signals;

and comparing the measurement object scatter diagram with a preset scatter diagram to determine the type information of the measurement object.

Alternatively, the first and second electrodes may be,

the step of acquiring type information of the measurement object includes:

and acquiring the type information of the measuring object according to a preset measuring mode.
The method according to any one of claims 1 to 3, wherein the step of acquiring detection values of the measurement object includes:

acquiring at least two optical signals of a forward scattered light signal, a side scattered light signal and a fluorescent signal of a particle in the measurement object;

and in response thereto,

the step of processing the detection value of the measurement object according to the type information of the measurement object includes:

the at least two optical signals are processed according to a classification algorithm related to the type information of the measurement object to classify and count particles in the measurement object, and/or the at least two optical signals, in particular fluorescence signals, are gain-amplified according to the type information of the measurement object.
The method of claim 4, wherein prior to the step of processing the at least two light signals according to a classification algorithm related to the type information of the measurement object, the method further comprises:

and acquiring the classification algorithm from a pre-stored classification algorithm database or through RFID or the Internet according to the type information of the measured object.
The method according to any one of claims 1 to 5, wherein the step of acquiring detection values of the measurement object includes:

acquiring volume distribution information of particles of a measurement object suspended in a diluent and a temperature of the diluent;

and in response thereto,

the step of processing the detection value of the measurement object according to the type information of the measurement object includes:

and correcting the volume distribution information by using a temperature correction algorithm related to the type information of the measuring object according to the temperature of the diluent.
The method according to claim 6, wherein before the step of correcting the volume distribution information using a temperature correction algorithm related to the type information of the measurement object according to the temperature of the dilution liquid, the method further comprises:

and acquiring the temperature correction algorithm from a pre-stored temperature correction algorithm database or through RFID or the Internet according to the type information of the measurement object.
The method according to claim 6 or 7, wherein the temperature correction algorithm is a temperature correction curve, which is a fitted curve, in particular a piecewise fitted curve, such as a first-order fitted curve or a second-order fitted curve, in particular a piecewise linear function, of the volume distribution information of the measurement object with respect to temperature.
The method of any one of claims 6 to 8, wherein the temperature correction algorithm corresponding to the blood sample is a negative correlation function of the volume distribution information of the blood sample and the temperature, and the temperature correction algorithm corresponding to the quality control substance or the calibration substance is a positive correlation function of the volume distribution information of the quality control substance or the calibration substance and the temperature.
The method of claim 7, wherein the method further comprises:

acquiring the batch of the diluent, and obtaining the temperature correction algorithm from a pre-stored temperature correction algorithm database or through RFID or the Internet according to the type information of the measurement object and the batch of the diluent.
The method of any one of claims 6 to 10, wherein the volume distribution information comprises mean cell volume and cell distribution width standard deviation.
The method of any of claims 6 to 11, wherein the method further comprises:

and calculating other parameter information of the measuring object related to the volume distribution information according to the corrected volume distribution information.
The method of claim 12, wherein the method further comprises:

outputting the volume distribution information before correction, the volume distribution information after correction and the other parameter information;

preferably, the corrected volume distribution information and the other parameter information are also marked.
A blood cell analyzer, wherein the blood cell analyzer comprises:

a sampling device configured to suck a measurement object;

the pretreatment device is used for pretreating the measurement object so as to obtain a pretreated measurement object;

the detection device is used for detecting the preprocessed measurement object;

a processor configured to perform the steps of:

acquiring type information of the measuring object;

acquiring a detection value of the measurement object;

and processing the detection value of the measurement object according to the type information of the measurement object.
The blood cell analyzer of claim 14, wherein the type information of the measurement object includes a blood sample, a quality control substance, or a calibrator.
The blood cell analyzer according to claim 14 or 15,

the processor is arranged for performing the following steps when performing the step of obtaining type information of the measurement object:

acquiring at least two optical signals of a forward scattered light signal, a side scattered light signal and a fluorescent signal of a particle in the measurement object;

forming a measurement object scattergram according to the at least two optical signals;

comparing the measurement object scatter diagram with a preset scatter diagram to determine the type information of the measurement object;

alternatively, the first and second electrodes may be,

the processor is configured to acquire type information of the measurement object according to a preset measurement mode when the step of acquiring the type information of the measurement object is performed.
The blood cell analyzer according to any one of claims 14 to 16,

the processor is configured to: acquiring at least two optical signals of a forward scattered light signal, a side scattered light signal, and a fluorescent signal of a particle in the measurement object when the step of acquiring a detection value of the measurement object is performed; and in performing the step of processing the detection value of the measurement object according to the type information of the measurement object, the at least two optical signals are processed according to a classification algorithm related to the type information of the measurement object to classify and count particles in the measurement object, and/or the at least two optical signals, particularly fluorescence signals, are gain-amplified according to the type information of the measurement object.
The blood cell analyzer according to claim 17,

the processor is further arranged for obtaining the classification algorithm from a pre-stored classification algorithm database or via RFID or internet in dependence of the type information of the measurement object before processing the at least two optical signals in dependence of the classification algorithm in dependence of the type information related to the measurement object.
The blood cell analyzer according to any one of claims 14 to 18, further comprising a sensing device provided to detect a temperature of a diluent in which the measurement object is located; and

the processor is configured to: acquiring volume distribution information of the measurement object suspended in the diluent and a temperature of the diluent when the step of acquiring the measurement value of the measurement object is performed; and correcting the volume distribution information by using a temperature correction algorithm associated with the type information of the measurement object, based on the temperature of the diluent, when the step of processing the detection value of the measurement object based on the type information of the measurement object is performed.
The blood cell analyzer according to claim 19,

the processor is configured to obtain the temperature correction algorithm from a pre-stored temperature correction algorithm database or through RFID or the internet according to the type information of the measurement object before performing the step of correcting the volume distribution information using the temperature correction algorithm associated with the type information of the measurement object according to the temperature of the diluent.
The hematology analyzer according to claim 19 or 20, wherein the temperature correction algorithm is a temperature correction curve, which is a fitted curve, in particular a piecewise fitted curve, such as a first-order fitted curve or a second-order fitted curve, in particular a piecewise linear function, of the volume distribution information of the measurement object with respect to temperature.
The hematology analyzer of any one of claims 19 to 21, wherein the temperature correction algorithm corresponding to the blood sample is a negative correlation function of the volume distribution information of the blood sample and the temperature, and the temperature correction algorithm corresponding to the quality control substance or the calibration substance is a positive correlation function of the volume distribution information of the quality control substance or the calibration substance and the temperature.
The blood cell analyzer according to any one of claims 19 to 22,

the processor is further configured to calculate other parameter information of the measurement object related to the volume distribution information according to the corrected volume distribution information.
The blood cell analyzer according to any one of claims 19 to 23,

the processor is further configured to output the volume distribution information before the correction, the volume distribution information after the correction, and the other parameter information; and marking the corrected volume distribution information and the other parameter information.
A computer-readable storage medium, on which a program is stored which, when being executed by a processor, carries out the steps of the method of processing a parameter of a measurement object according to any one of claims 1 to 13.