A method for distinguishing particle communities, a particle analysis device, and a storage medium

Abstract

The present application discloses a method for distinguishing particle communities, a particle analysis device, and a storage medium. The method includes: obtaining a particle characteristic distribution histogram; wherein, the first-direction coordinate of the particle characteristic distribution histogram is a channel representing particle characteristics, and the second-direction coordinate of the particle characteristic distribution histogram is the number of particles; determining a particle intersection region in the particle characteristic distribution histogram; determining a reference line located within the intersection region, wherein the reference line extends along the first direction; generating a corresponding flipped histogram according to the particle characteristic distribution histogram and the reference line; and determining the boundary line of the particle community according to the flipped histogram to distinguish the particle communities. In this way, different particle communities can be stably and accurately distinguished.

Description

Technical Field

[0001] The present application relates to the field of blood analysis, and particularly to a method for distinguishing particle communities, a particle analysis device, and a storage medium. Background Art

[0002] Blood cell analysis is one of the most widely used inspection items in clinical medical tests. Currently, automatic blood cell analyzers are commonly used at home and abroad to automatically detect anticoagulated whole blood, and parameters such as the number of white blood cells (WBC), the number of red blood cells (RBC), the number of platelets (PLT), the mean corpuscular volume (MCV) of red blood cells, the mean platelet volume (MPV), etc. are given. These parameters will help clinicians and laboratory technicians correctly analyze the test results and provide evidence for clinical diagnosis.

[0003] Currently, most blood cell analyses mainly use the impedance method for platelet analysis. When using the impedance method for red blood cell and platelet determination, generally, the cell volume size is used as the basis for classifying various cells. The pulse voltage corresponding to each cell is corresponding to the cell volume, and this corresponding relationship is plotted and transformed into a histogram. By finding the lowest point in the intersection area of different volume communities in the histogram as the dividing line, different particle communities are distinguished. However, such a method may lack a certain degree of stability. Summary of the Invention

[0004] To solve the above problems, the present application provides a method for distinguishing particle communities, a particle analysis device, and a storage medium, which can stably and accurately distinguish different particle communities.

[0005] To solve the above technical problems, a technical solution adopted by the present application is: to provide a method for distinguishing particle communities, the method including: obtaining a particle characteristic distribution histogram; wherein, the first direction coordinate of the particle characteristic distribution histogram is a channel representing particle characteristics, and the second direction coordinate of the particle characteristic distribution histogram is the number of particles; determining a particle intersection area in the particle characteristic distribution histogram; determining a reference line located within the intersection area, wherein the reference line extends along the first direction; generating a corresponding flipped histogram according to the particle characteristic distribution histogram and the reference line; and determining the dividing line of the particle community according to the flipped histogram to distinguish the particle community.

[0006] Wherein, determining a particle intersection area in the particle characteristic distribution histogram includes: determining a left boundary in the particle characteristic distribution histogram; and determining a right boundary in the particle characteristic distribution histogram; and determining the particle intersection area based on the left boundary and the right boundary.

[0007] Among them, determining the left boundary in the particle characteristic distribution histogram includes: determining a preset channel range in the particle characteristic distribution histogram; determining the corresponding left boundary according to the channel corresponding to the maximum number of particles in the preset channel range; or determining the corresponding left boundary according to any channel within a preset number of particles to the right of the channel corresponding to the maximum number of particles in the preset channel range.

[0008] Among them, determining the right boundary in the particle characteristic distribution histogram includes: determining the right boundary at a preset channel interval to the right of the left boundary.

[0009] Among them, the preset channel interval is positively correlated with the total number of particles within the preset channel range.

[0010] Among them, the number of particles corresponding to the reference line is not less than the number of particles corresponding to the right boundary; or the number of particles corresponding to the reference line is not less than the number of particles corresponding to any channel within a preset number of particles to the left of the right boundary.

[0011] Among them, generating a corresponding flipped histogram according to the particle characteristic distribution histogram and the reference line includes: subtracting the height of the particle characteristic distribution histogram from the height of the reference line to obtain the corresponding flipped histogram.

[0012] Among them, determining the dividing line of the particle community according to the flipped histogram to distinguish the particle community includes: calculating the dividing line using the following formula: Among them, M k is the dividing line of the particle community, i is the channel value in the flipped histogram, f(i) is the value of the flipped histogram at the i-th channel, g(·) is a processing function, and satisfies: g(x)≥g(y)≥0.

[0013] To solve the above technical problems, another technical solution adopted by this application is: providing a particle analysis device, which includes a processor and a memory. The memory stores a computer program, and when the computer program is executed by the processor, it is used to implement the above method for distinguishing particle communities.

[0014] To solve the above technical problems, yet another technical solution adopted by this application is: providing a computer-readable storage medium for storing a computer program, and when the computer program is executed by the processor, it is used to implement the above method for distinguishing particle communities.

[0015] The beneficial effects of the embodiments of this application are as follows: Different from the prior art, the method for distinguishing particle communities provided in this application determines the particle intersection region in the obtained particle characteristic distribution histogram, determines the reference line located within the intersection region, further generates the corresponding flipped histogram based on the particle characteristic distribution histogram and the reference line, and finally determines the boundary line of the particle community based on the flipped histogram to achieve the distinction of particle communities. In this way, on the one hand, using the flipped histogram to determine the boundary line of the particle community can improve the accuracy of distinguishing particle communities; on the other hand, by first determining the particle intersection region and then determining the reference line, it can be applied to different blood samples, has a certain stability, and can further improve the accuracy of distinguishing particle communities. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] To more clearly illustrate the technical solutions in the embodiments of this application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of this application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings. Among them:

[0017] Figure 1 is a schematic flowchart of the first embodiment of the method for distinguishing particle communities provided in this application;

[0018] Figure 2 is a schematic diagram of the voltage pulse when particles pass through the micropores;

[0019] Figure 3 is a schematic diagram of the distribution of platelets and red blood cells;

[0020] Figure 4 is a schematic flowchart of the second embodiment of the method for distinguishing particle communities provided in this application;

[0021] Figure 5 is Figure 4 the specific flowchart of S42 in

[0022] Figure 6 is a particle characteristic distribution histogram provided in this application;

[0023] Figure 7 is Figure 6 the corresponding flipped histogram;

[0024] Figure 8 is a schematic flowchart of the third embodiment of the method for distinguishing particle communities provided in this application;

[0025] Figure 9 is a schematic flowchart of the fourth embodiment of the method for distinguishing particle communities provided in this application;

[0026] Figure 10 It is a schematic diagram of a preset channel range;

[0027] Figure 11 It is another particle characteristic distribution histogram provided by the present application;

[0028] Figure 12 It is Figure 11 The corresponding flipped histogram;

[0029] Figure 13 It is a schematic structural diagram of an embodiment of a particle analysis device provided by the present application;

[0030] Figure 14 It is a schematic structural diagram of an embodiment of a computer-readable storage medium provided by the present application. Specific embodiments

[0031] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. It can be understood that the specific embodiments described herein are only used to explain the present application, rather than limiting the present application. In addition, it should be noted that for the sake of description, only parts related to the present application rather than all structures are shown in the accompanying drawings. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present application.

[0032] Referring to "embodiment" herein means that the specific features, structures, or characteristics described in conjunction with the embodiment may be included in at least one embodiment of the present application. The phrase appears in various positions in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein may be combined with other embodiments.

[0033] Refer to Figure 1 , Figure 1 It is a schematic flowchart of the first embodiment of the method for distinguishing particle communities provided by the present application. The method of this embodiment specifically includes:

[0034] S11: Obtain a particle characteristic distribution histogram.

[0035] In this embodiment, the particle characteristic distribution histogram is obtained by statistically measuring a blood sample solution using a blood cell analyzer (particle analyzer). Generally, a blood cell analyzer includes a holding tank, a micropore, a power component, and an analysis circuit. When analyzing blood cells using a blood cell analyzer, a certain amount of the blood sample to be tested is added to a certain amount of a diluent having particle morphology and electrical conductivity characteristics, and then the formed mixture is drawn into the channel of the micropore under the action of the power component. When each particle passes through this micropore, since the particle replaces an equal volume of the electrolyte solution and has a relatively weak electrical conductivity characteristic, the passing of the particle increases the equivalent impedance of the micropore. As Figure 2 shown, under the action of the power component, the change in voltage is proportional to the change in impedance. Thus, when a particle passes through micropore O, a pulse voltage will be generated accordingly. The height of this voltage pulse reflects the characteristics of the particle.

[0036] Furthermore, the analysis circuit will count all the particles in the mixed solution into the corresponding channels of the particle characteristic distribution histogram according to the particle characteristics, that is, the particles corresponding to the same height of voltage are counted into the same channel, thereby cumulatively obtaining a particle characteristic distribution histogram with the first direction (abscissa direction) representing the particle characteristics and the second direction (ordinate direction) representing the particle number. Among them, since there are obvious differences in the volumes of platelets and red blood cells, in this embodiment, the particle characteristic is the volume of the particle.

[0037] Take Figure 3 as an example to briefly illustrate the particle characteristic distribution histogram. As shown in the figure, Figure 3 is a distribution schematic diagram of platelets and red blood cells. The curve in the figure can be called the volume / particle number curve, which is used to represent the volume distribution of different particles. Since under normal circumstances, red blood cells have a larger volume, platelets have a smaller volume, there are more red blood cells, and fewer platelets, and the number of platelets in a normal person is 1 / 20 of the number of red blood cells. Red blood cells are mainly distributed in the range of 40 femtoliters to 130 femtoliters, and platelets are mainly distributed in the range of 2 femtoliters to 25 femtoliters. Therefore, it can be clearly seen that the figure is divided into two different communities of platelets and red blood cells. The platelet community is distributed in the lower volume range segment, and the red blood cell community is distributed in the higher volume range segment.

[0038] It can be known that the mixed solution passing through the micropore mainly includes three types of particles: white blood cells, red blood cells, and platelets. Any cell will generate a pulse when passing through the micropore. Therefore, through the pulse, only the distribution and quantity of all cells in the blood sample to be tested can be known, but the types of cells cannot be distinguished. And the volume of white blood cells in the blood is relatively large, and the quantity is much smaller than that of red blood cells and platelets. Therefore, when distinguishing different particle communities, the influence brought by white blood cells can be ignored.

[0039] S12: Determine the particle intersection region in the particle characteristic distribution histogram.

[0040] Among them, the particle intersection region refers to the part where the platelet community and the red blood cell community meet. For Figure 3 example, it usually refers to the trough part between the platelet community and the red blood cell community. The specific intersection region needs to be determined or adjusted according to the actual situation. For example, when the trough feature is not obvious, it is necessary to accurately define the particle intersection region through certain calculations or historical experience to improve the accuracy of the subsequent boundary line calculation.

[0041] In this embodiment, the particle intersection region can be a channel distribution range representing a certain volume, and there is a corresponding part of the volume / particle number curve within this channel distribution range; in other embodiments, the particle intersection region can also be square, such as rectangular, and the length and width of the rectangle are parallel to the first direction or the second direction respectively, so as to determine the particle intersection region in the histogram. Among them, the actual boundary line between the platelet community and the red blood cell community is included in the particle intersection region, which can distinguish platelets and red blood cells.

[0042] S13: Determine the reference line located within the intersection region.

[0043] Among them, the reference line extends along the first direction, indicating that between the reference line and the horizontal coordinate axis, at least in their respective extension directions, they are the same. Specifically, they may be parallel to each other in the extension direction, or may not be parallel but also do not intersect in the extension direction.

[0044] In some embodiments, the reference line can be parallel to the first direction, and the distance between it and the first direction represents the reference flip height RefH (Reference Height) of the reference line. In this embodiment, the specific position setting of the reference line is related to the particle intersection region of the histogram, specifically related to the height of the volume / particle number curve within the particle intersection region. The existence of the reference line is equivalent to setting a reference standard value for the curve in the particle intersection region, which can set the particle numbers of all channels within the intersection region under a reasonable standard, so as to facilitate the subsequent calculation and determination of the boundary line based on the particle numbers under this standard.

[0045] In some other embodiments, the reference line can also be a curve. In this case, the reference line is not parallel to the first direction, and the specific position of the reference line is set according to the volume channel value in the first direction and / or the particle number value in the second direction. The curve-shaped reference line obtained in this way can adapt to the volume / particle number curves in different particle characteristic distribution histograms, so as to ensure the stable generation of the subsequent flipped histogram when the change of the volume / particle number curve in the intersection region is not obvious. In this embodiment and subsequent embodiments, the reference line is preferably a straight line and is set parallel to the first direction.

[0046] S14: Generate a corresponding flipped histogram according to the particle characteristic distribution histogram and the reference line.

[0047] Among them, the flipped histogram is a histogram formed by flipping the particle characteristic distribution histogram according to the reference line, and is also called an equivalent negative histogram in some other embodiments. In each volume channel in the particle intersection region, there is the same or different height difference (distance) between all reference lines and the corresponding volume / particle number curves. The height difference of different channels is the height value of the corresponding channel in the flipped histogram, and thus a flipped histogram corresponding to the particle intersection region is generated. The particle population represented in the flipped histogram is the flipped particle population.

[0048] S15: Determine the boundary line of the particle population according to the flipped histogram to distinguish the particle populations.

[0049] Among them, the boundary line of the particle population refers to the target straight line that can be used to distinguish different particle populations. When the calculated boundary line is accurate enough, the platelet population should be on the left side of the boundary line of the particle characteristic distribution histogram, and the red blood cell population should be on the right side.

[0050] It can be known that in the particle characteristic distribution histogram obtained from a normal blood sample, the boundary line should theoretically be the lowest point of the volume / particle number curve in the particle intersection region. However, when it is necessary to distinguish the particle populations of abnormal blood samples with low concentrations, the lowest point in the particle intersection region may not be the actual lowest point, and in this case, the accuracy of distinguishing the particle populations cannot be guaranteed.

[0051] Therefore, in this embodiment, by converting the particle intersection region of platelets and red blood cells into a flipped histogram, it is equivalent to converting the goal of finding the lowest point in the particle intersection region into finding the highest point in the flipped histogram, and then according to a preset formula, calculating the maximum statistic of the flipped particle population in the flipped histogram. The maximum statistic represents the value of the volume channel, that is, the lowest point in the corresponding particle intersection region. Finally, the channel where the boundary line between platelets and red blood cells is located in the corresponding particle characteristic distribution histogram can be determined, so as to accurately distinguish the platelet population and the red blood cell population.

[0052] Further, the method for determining the demarcation line in this embodiment can be applied to different blood samples (including normal, abnormal or low-concentration samples). When determining the intersection area, it can adaptively determine the particle intersection area according to the actual situation of the trough in the particle characteristic distribution histogram. Then, when determining the reference line, it can adaptively determine the reference line according to the actual situation of the volume / particle number curve within the particle intersection area. Such a method can further improve the calculation accuracy of the demarcation line, thereby further improving the accuracy of distinguishing particle communities.

[0053] Different from the prior art, the method for distinguishing particle communities provided in this embodiment determines the particle intersection area in the obtained particle characteristic distribution histogram, determines the reference line located within the intersection area, further generates the corresponding flipped histogram according to the particle characteristic distribution histogram and the reference line, and finally determines the demarcation line of the particle community based on the flipped histogram to achieve the distinction of the particle community. In this way, on the one hand, using the flipped histogram to determine the demarcation line of the particle community can improve the accuracy of distinguishing particle communities; on the other hand, by first determining the particle intersection area and then determining the reference line, it can be applied to different blood samples, has a certain stability, and can further improve the accuracy of distinguishing particle communities.

[0054] Refer to Figure 4 , Figure 4 which is a schematic flowchart of the second embodiment of the method for distinguishing particle communities provided by this application. The method of this embodiment specifically includes:

[0055] S41: Obtain the particle characteristic distribution histogram.

[0056] Among them, the first direction coordinate of the particle characteristic distribution histogram is the channel representing the particle characteristic, and the second direction coordinate of the particle characteristic distribution histogram is the particle number. In this embodiment, the particle characteristic is the volume of the particle.

[0057] S42: Determine the left boundary in the particle characteristic distribution histogram.

[0058] Among them, the left boundary corresponds to a certain volume channel. Optionally, the left boundary can be preset according to historical experience. For example, after obtaining the analysis and statistical information of multiple historical blood samples, the analyzer operator combines the historical particle characteristic distribution histogram to analyze and predict the volume channel corresponding to the maximum number of platelet particles, the volume channel corresponding to the maximum number of red blood cell particles, and the volume channel where the demarcation line between platelets and red blood cells is located in the information, so as to obtain a preset value of the left boundary and input the preset value into the instrument in advance, then the left boundary of the current particle characteristic distribution histogram can be obtained.

[0059] Optionally, S42 can be implemented through Figure 5 the method steps shown below, specifically including:

[0060] S421: Determine a preset channel range in the particle characteristic distribution histogram.

[0061] Among them, the preset channel range refers to the channel distribution range of platelet community volume. It can also be based on the experience of the analyzer operator. After observing the historical particle characteristic distribution histogram or combining historical analysis and statistical information, the operator can preset a channel range according to experience and input it into the instrument to obtain the preset channel range of the current particle characteristic distribution histogram. This method can effectively improve the accuracy of the preset channel range when the curve change characteristics of the histogram are not obvious.

[0062] In some embodiments, the left boundary can be determined in the manner of S422:

[0063] S422: Determine the corresponding left boundary according to the channel corresponding to the maximum value of the number of particles in the preset channel range.

[0064] Among them, the maximum value of the number of particles is expressed as the highest point in the second direction within the preset channel range of the particle characteristic distribution histogram, and the left boundary is the volume channel position corresponding to the highest point.

[0065] In some other embodiments, the left boundary can be determined in the manner of S423:

[0066] S423: Determine the corresponding left boundary according to any channel within the preset number of particles range on the right side of the maximum value of the number of particles in the preset channel range.

[0067] Among them, the preset number of particles range refers to a particle number interval with the maximum value of the number of particles as the starting point of the range and 80% of the maximum value of the number of particles as the ending point of the range, and the ending point is located on the right side of the starting point. When there are multiple ending points of the same size, select the nearest point. Therefore, the part between the starting point and the ending point is the preset number of particles range, and the left boundary at this time should be any channel within the channel corresponding to the starting point (maximum value) to the channel corresponding to the ending point (80% of the maximum value). For example, if the maximum value of the number of particles in the preset channel range is 10 units, the corresponding channel is 15, and 80% of the maximum value of the number of particles is 8 units, and the corresponding channel is 20, so the left boundary is any one within the channels from 15 to 20. Specifically, it can be selected according to the actual situation. For example, the most stable one can be determined through variance calculation, and the setting of 80% can also be adjusted according to the actual situation. For example, it can also be 85%, 90%, 95%, etc. No more restrictions are made here.

[0068] S43: Determine the right boundary in the particle characteristic distribution histogram.

[0069] Among them, the right boundary corresponds to a certain volume channel; optionally, the right boundary can also be preset according to historical experience, for example, set in the manner described above, and will not be elaborated here.

[0070] Optionally, S43 can also be implemented through the following steps: Determine the right boundary at a preset channel interval to the right of the left boundary.

[0071] Among them, the preset channel interval is expressed as a range of channel intervals, and the preset channel interval is positively correlated with the total number of particles within the preset channel range, that is, the channel number of the right boundary = the channel number of the left boundary + the channel number of the preset channel interval. Specifically, since the preset channel range represents the channel distribution range of the platelet community volume, the number of platelet particles within the preset channel range is certain. When the number of platelet particles within the preset channel range is larger, the corresponding channel interval range of the preset channel interval is larger, and at this time, the interval between the right boundary and the left boundary will be farther. Thus, the channel position of the right boundary can be determined based on the left boundary and the preset channel interval.

[0072] S44: Determine the particle intersection region based on the left boundary and the right boundary.

[0073] As Figure 6 shown, Figure 6 is a particle characteristic distribution histogram provided by the present application. It can be seen that the particle intersection region is a range of channel distributions, which is used to represent the intersecting part between platelets and red blood cells. The dashed line A near the left side is the left boundary A, and the dashed line B near the right side is the right boundary B, and both the dashed line A and the dashed line B are parallel to the second direction. The particle intersection region determined in this way can be in a more reasonable channel range, and some channels that are clearly not part of the boundary can be excluded from the particle intersection region, or when the trough feature of the curve is not obvious, the intersection region can be accurately defined through the above method, thereby improving the accuracy of subsequent boundary line calculation.

[0074] S45: Determine the reference line located within the intersection region.

[0075] Continue to refer to Figure 6 , the horizontal dashed line C in the figure is the reference line C, and its height represents the reference flip height RefH. The reference line C is parallel to the first direction. In some embodiments, the number of particles corresponding to the reference line C is not less than the number of particles corresponding to the right boundary B, that is to say, the height of the example reference line C in the figure needs to be greater than the height of the channel corresponding to the right boundary B. And since the height of the channel corresponding to the right boundary B is usually also greater than the height of the channel corresponding to the left boundary A, the height of the reference line C should be greater than the corresponding height of all channels in the particle intersection region.

[0076] In some other embodiments, the number of particles corresponding to the reference line C is not less than the number of particles corresponding to any channel within the preset particle number range to the left of the right boundary B. Among them, the preset particle number range is the same as described above, which refers to a particle number interval with the particle number corresponding to the channel of the right boundary B as the starting point of the range and 80% of the particle number corresponding to the channel of the right boundary B as the ending point of the range, and the ending point of the range is located to the left of the starting point of the range. That is to say, at this time, the height of the reference line C needs to be greater than multiple heights within the channels corresponding to the starting point to the ending point; further, the multiple heights can be specifically determined according to the actual situation, and the setting of 80% can also be adjusted according to the actual situation. For example, it can also be 85%, 90%, 95%, etc.

[0077] S46: Subtract the height of the particle characteristic distribution histogram from the height of the reference line to obtain the corresponding flipped histogram.

[0078] Among them, for outside the particle intersection region, the height of the flipped histogram is determined to be 0. For within the particle intersection region, the height of the flipped histogram is the height value obtained by subtracting the height of the particle characteristic histogram from the height of the reference line C, that is, the height difference between the reference line C and the corresponding volume / particle number curve.

[0079] In this embodiment, the flipped histogram mainly corresponds to the particle intersection region. The height of the particle characteristic distribution histogram is the height corresponding to multiple volume channels within the particle intersection region. Within each volume channel of the particle intersection region, there is the same or different height difference between the reference line C and the corresponding volume / particle number curve. The height difference of different channels is the height value of the corresponding channel in the flipped histogram. Therefore, subtracting the height of the particle characteristic histogram from the height of the reference line C can obtain the corresponding flipped histogram. The flipped histogram is specifically as Figure 7 shown, and the particle community represented in the flipped histogram is the flipped particle community.

[0080] S47: Determine the boundary line of the particle community according to the flipped histogram to distinguish the particle community.

[0081] Optionally, the boundary line of the particle community can be calculated using the following formula:

[0082]

[0083] where M k is the boundary line of the particle community, that is, the boundary line between the two communities of platelets and red blood cells, corresponding to a certain volume channel; i is the channel value in the flipped histogram, corresponding to the volume size of the particle, f(i) is the value of the flipped histogram at the i-th channel, and g(·) is a processing function and satisfies: g(x) ≥ g(y) ≥ 0.

[0084] In this embodiment, by transforming the particle intersection region of platelets and red blood cells into a flipped histogram, it is equivalent to transforming the goal of finding the lowest point of the particle intersection region into finding the highest point in the flipped histogram, and the above formula can be used to characterize the highest point of the flipped histogram from a statistical perspective, that is, the lowest point corresponding to the particle intersection region. Finally, the channel where the boundary between platelets and red blood cells is located in the corresponding particle characteristic distribution histogram can be determined, thereby accurately distinguishing the platelet community and the red blood cell community.

[0085] For the above formula, after expanding it, it can be found that the essence of the formula is actually a weighted sum of the volume sizes corresponding to all channels, and for the weight value of each channel, it is determined by the number of particles at the current channel of the flipped histogram. For example, the weight value ai of the i-th channel is jointly determined by the value obtained by processing the height of the i-th channel in the flipped histogram through the function g(·) and the sum of the heights of all channels in the entire flipped histogram processed through the function g(·). Since the function g(·) satisfies g(x) ≥ g(y) ≥ 0, therefore, the higher the height of the channel in the flipped histogram, the larger the corresponding weight value ai, that is, the channel i has a higher weight proportion in M k . Therefore, M calculated in this way k should be relatively close to the actual highest point in the flipped histogram, so that the boundary of the particle community can be accurately determined and used to distinguish platelets and red blood cells. Among them, the processing function of this embodiment can be

[0086] Moreover, in this embodiment, since the number of particles corresponding to the reference line in the particle characteristic distribution histogram is not less than the number of particles corresponding to the right boundary, or not less than the number of particles corresponding to any channel within the preset particle number range on the left side of the right boundary, such a method makes the method of this embodiment have a certain adaptability and can adapt to different blood samples. Especially when there are abnormal blood samples with low concentrations, it can be well solved.

[0087] For example, when the upper limit of the platelet volume and the lower limit of the red blood cell volume in the sample are quite close, at this time, the determination of the particle intersection region and the reference line will become particularly important. If the range of the intersection region is too large or too small, it may lead to a large error when calculating the boundary, resulting in a poor result of distinguishing the particle community. However, the method of this embodiment can reasonably avoid such errors using some rules and improve the accuracy of the boundary.

[0088] For the determination of the reference line, if the height of the reference line is set too low, the difference between the height of the reference line and the height of each channel is small at this time, resulting in a small number of particles in each channel of the flipped histogram. Since the basis for calculating the demarcation line by the above preset formula is related to the weight and the weight ratio, when the height difference is small, it may lead to errors in the weights corresponding to each channel of the flipped particle community, or even errors in the weight ratio, thus obtaining a demarcation line with poor accuracy. The method of this embodiment sets the height of the reference line to be not lower than the height corresponding to the right boundary, which can increase the height difference between the reference line and each channel, thereby reducing the problem of low accuracy of the demarcation line caused by weight errors. Therefore, by reasonably determining the particle intersection area and further reasonably setting the reference line on the basis of the particle intersection area, the accuracy rate of demarcation line calculation can be jointly improved.

[0089] It should be noted that this embodiment does not limit the upper limit of the height of the reference line. In some embodiments, the specific setting of the reference line may not be limited to the above two situations. On the premise of ensuring the calculation accuracy, the height of the reference line can even be much greater than the height corresponding to the right boundary. For example, the height of the reference line is N times the height corresponding to the right boundary, where the value of N can be set according to the upper and lower limits of the volume of different particle communities, or can also be set according to the highest and lowest points of the channels existing in the particle intersection area, so that the reference line obtained according to the reasonable setting method can adapt to various different blood samples, has a certain stability, and accurately calculates the demarcation line based on the preset formula.

[0090] Refer to Figure 8 , Figure 8 is a schematic flowchart of the third embodiment of the method for distinguishing particle communities provided by this application. The method of this embodiment specifically includes:

[0091] S81: Obtain a histogram of particle characteristic distribution.

[0092] Among them, the first direction coordinate of the histogram of particle characteristic distribution is the channel representing particle characteristics, and the second direction coordinate of the histogram of particle characteristic distribution is the number of particles. In this embodiment, since there are obvious differences in the volumes of platelets and red blood cells, the particle characteristic is the volume of the particle.

[0093] Among them, the histogram of particle characteristic distribution is obtained by statistically measuring a blood sample solution using a blood cell analyzer. The specific principle is introduced in the foregoing embodiments and will not be elaborated here.

[0094] S82: Determine the left boundary in the histogram of particle characteristic distribution, and within the preset channel range on the right side of the left boundary, determine the right boundary based on the maximum value of the number of particles, and determine the particle intersection area based on the left boundary and the right boundary.

[0095] Among them, the particle intersection region refers to the part where the platelet community and the red blood cell community intersect, usually the trough part between the platelet community and the red blood cell community. The specific intersection region needs to be determined or adjusted according to the actual situation. For example, when the trough feature is not obvious, it is necessary to accurately define the particle intersection region through certain calculations or historical experience to improve the accuracy of the subsequent boundary line calculation.

[0096] In this embodiment, the left boundary corresponds to a certain volume channel, and the left boundary can be determined according to the number of specific particles within a certain volume range. For example, in the volume channel of the platelet community, the channel with the largest number of particles is used as the channel corresponding to the left boundary, or a channel adjacent to the right of the channel with the largest number of particles in the volume range of the platelet community is used as the channel corresponding to the left boundary. There is no limitation here, and it can be set according to the actual situation.

[0097] Among them, the preset channel range refers to the channel distribution range of the estimated target particles. In this embodiment, it can specifically be the channel distribution range of the platelet community, which is usually preset based on the experience of the analyzer operator. A maximum particle number is determined within the preset channel range, which is the right boundary. Thus, the particle intersection region is determined based on the left boundary and the right boundary. The particle intersection region is represented as a special channel distribution range. There is a part of the volume / particle number curve corresponding within this channel distribution range, and it includes the actual boundary line between the platelet community and the red blood cell community, which can distinguish platelets and red blood cells.

[0098] S83: Determine the reference line located within the intersection region.

[0099] Among them, the reference line is parallel to the first direction, and the distance between the reference line and the first direction represents the reference flip height RefH (Reference Height, reference dimension height) of the reference line. In this embodiment, the specific position setting of the reference line is related to the particle intersection region of the histogram, specifically related to the height of the volume / particle number curve within the particle intersection region. The existence of the reference line is equivalent to setting a reference standard value for the curve in the particle intersection region, which can set the number of particles in all channels within the intersection region under a reasonable standard, so as to facilitate the subsequent calculation and determination of the boundary line based on the number of particles under this standard.

[0100] S84: Generate a corresponding flipped histogram according to the particle characteristic distribution histogram and the reference line.

[0101] Among them, the flipped histogram is a histogram formed by flipping the particle characteristic distribution histogram according to the reference line, and is also called the equivalent negative histogram in some other embodiments. In each volume channel of the particle intersection region, there is the same or different height difference (distance) between all reference lines and the corresponding volume / particle number curves. The height difference of different channels is the height value of the corresponding channel of the flipped histogram, and thus a flipped histogram corresponding to the particle intersection region is generated. The particle community represented in the flipped histogram is the flipped particle community.

[0102] S85: Determine the boundary line of the particle community according to the flipped histogram to distinguish the particle community.

[0103] In this embodiment, by converting the particle intersection region of platelets and red blood cells into a flipped histogram, it is equivalent to converting the goal of finding the lowest point of the particle intersection region into finding the highest point in the flipped histogram. Then, according to the preset formula, calculate the maximum statistic of the flipped particle community in the flipped histogram. The maximum statistic represents the value of the volume channel, that is, the lowest point in the corresponding particle intersection region. Finally, the channel where the boundary line between platelets and red blood cells is located in the corresponding particle characteristic distribution histogram can be determined, so as to accurately distinguish the platelet community and the red blood cell community.

[0104] Furthermore, the method for determining the boundary line in this embodiment can be applied to different blood samples (including normal, abnormal or low-concentration samples). When determining the intersection region, the particle intersection region can be adaptively determined according to the actual situation of the trough in the particle characteristic distribution histogram; then when determining the reference line, the reference line can be adaptively determined according to the actual situation of the volume / particle number curve in the particle intersection region. Such a method can further improve the calculation accuracy of the boundary line, and thus further improve the accuracy of distinguishing the particle community.

[0105] Different from the prior art, the method for distinguishing particle communities provided in this embodiment determines the left boundary and the right boundary in the obtained particle characteristic distribution histogram, determines the particle intersection region based on the left boundary and the right boundary, determines the reference line located in the intersection region, further generates the corresponding flipped histogram according to the particle characteristic distribution histogram and the reference line, and finally determines the boundary line of the particle community based on the flipped histogram to achieve the distinction of the particle community. In this way, on the one hand, using the flipped histogram to determine the boundary line of the particle community can improve the accuracy of distinguishing the particle community; on the other hand, by first determining the particle intersection region and then determining the reference line, it can be applied to different blood samples, has a certain stability, and can further improve the accuracy of distinguishing the particle community.

[0106] Refer to Figure 9 ,Figure 9 FIG. Figure 9 is a schematic flowchart of the fourth embodiment of the method for distinguishing particle communities provided by the present application. The method of this embodiment specifically includes:

[0107] S91: Obtain a particle characteristic distribution histogram.

[0108] Among them, the first-direction coordinate of the particle characteristic distribution histogram is the channel representing the particle characteristic, and the second-direction coordinate of the particle characteristic distribution histogram is the particle number. In this embodiment, the particle characteristic is the volume of the particle.

[0109] S92: Determine a first preset channel range in the particle characteristic distribution histogram.

[0110] Among them, the first preset channel range is a part of the channel distribution range of the estimated target particles. Specifically, in this embodiment, it can be the channel distribution range of the platelet community. The first preset channel range is used to determine the left boundary of the intersection area and can be preset according to historical experience. For example, after obtaining the analysis and statistical information of multiple historical blood samples, the analyzer operator analyzes in combination with the historical particle characteristic distribution histogram, so as to obtain different multiple historical left boundary information. Further, the first preset channel range can be determined according to this part of historical left boundary information and input into the instrument by the operator for use in the current or subsequent particle characteristic histograms.

[0111] S93: Determine the left boundary corresponding to the maximum particle number within the first preset channel range.

[0112] Refer to Figure 10 Figure 10 , which is a schematic diagram of the preset channel range. As shown in the figure, the range represented by X1 is the first preset channel range. It can be clearly seen from the figure that there is a highest point Max1 in the first preset channel range, indicating that the particle number corresponding to the volume channel of this point is the largest in X1, and thus the left boundary channel can be determined. In some other embodiments, the left boundary channel can also be the channel adjacent to the right of the channel corresponding to the maximum particle number. This is not limited herein and can be set according to actual situations.

[0113] Optionally, when there are multiple maximum particle numbers within the first preset channel range, the particle numbers of the left and right Q channels adjacent to the channels corresponding to the multiple maximum particle numbers can be calculated respectively to obtain the differences between the particle numbers of the Q channels and the maximum particle number respectively. Further, select the channel corresponding to the maximum particle number of the Q channels with the smallest difference as the left boundary channel. Among them, Q can be 5-10.

[0114] S94: Determine the minimum particle number within the second preset channel range on the right side of the left boundary.

[0115] As​Figure 10 As shown, the range represented by X2 is the second preset channel range. The second preset channel range is another part of the channel distribution range of the estimated target particles. It can be clearly seen from the figure that there is a lowest point Min in the second preset channel range, indicating that the number of particles in the volume channel corresponding to this point is the smallest in X2. Thus, the channel corresponding to the lowest point Min can be determined as the middle channel.

[0116] S95: Determine the right boundary corresponding to the maximum number of particles within the third preset channel range on the right side of the channel corresponding to the minimum number of particles.

[0117] As Figure 10 shown, the range represented by X3 is the third preset channel range. The third preset channel range is defined with the channel corresponding to the lowest point Min within X2 as the starting point of the range, and a channel with a certain number of channels spaced to the right of the channel corresponding to Min as the ending point of the range, thus forming the third preset channel range. It can be clearly seen from the figure that there is a highest point Max2 within the third preset channel range, indicating that the number of particles in the volume channel corresponding to this point is the largest in X3. Thus, it can be determined as the right boundary channel.

[0118] In some other embodiments, for the determination of the left boundary and the right boundary, it can also be determined based on any channel within the preset particle number range on the right or left side of the highest point Max1 of X1, and any channel within the preset particle number range on the left or right side of the highest point Max2 of X3. The specific method is similar to the foregoing embodiments and will not be elaborated here.

[0119] Optionally, X1, X2, and X3 can all be preset channel ranges based on historical experience, which can be used to accurately define the ranges of the left boundary and the right boundary, thus adapting to different samples.

[0120] Optionally, the second preset channel range can be a fixed value, and its specific position needs to be determined by the first preset channel range. That is to say, the size of the second preset channel range can remain unchanged, while the size of the first preset channel range may change, and specifically, it needs to be set according to the actual situation. Further, the third preset channel range can also be a fixed value, and its specific position changes according to the specific position of the lowest point Min within the second preset channel range. Therefore, the ending point of the third preset channel range may be within the ending point of the second preset channel range, may be outside the ending point of the second preset channel range, or may coincide with the ending point of the second preset channel range. The intersection area determined in this way has a certain adaptability and can improve the calculation accuracy of the subsequent demarcation line.

[0121] S96: Determine the particle intersection area based on the left boundary and the right boundary.

[0122] Referring to 11, Figure 11 Another particle characteristic distribution histogram provided for this application can be seen. The particle intersection region is a range of channel distribution, which is used to represent the intersecting part between platelets and red blood cells. The dotted line D near the left is the left boundary D, and the dotted line E near the right is the right boundary E. And both the dotted line D and the dotted line E are parallel to the second direction. Among them, the number of particles corresponding to the right boundary E of the channel is greater than the number of particles corresponding to the left boundary D of the channel. The particle intersection region determined in this way can be in a more reasonable channel range, and some channels that are clearly not part of the dividing line can be excluded from the particle intersection region. Or when the trough feature of the curve is not obvious, the intersection region can be accurately defined by the above method, so as to improve the accuracy of subsequent dividing line calculation.

[0123] S97: Determine the reference line located within the intersection region.

[0124] Continue to refer to Figure 11 , the horizontal dotted line F in the figure is the reference line F, and its height represents the reference flip height RefH. The reference line F is parallel to the first direction. In this embodiment, the number of particles corresponding to the reference line F is not less than the minimum value of the number of particles, that is, not less than the number of particles corresponding to the middle channel, that is, the height corresponding to the reference line F needs to be greater than the lowest point Min( Figure 11 (not shown in

[0125] In a specific embodiment, the number of particles corresponding to the reference line can be equal to:

[0126] 0.3*MIN(m1, m2)+0.7*m3, where m1 is the number of particles corresponding to the left boundary, m2 is the number of particles corresponding to the right boundary, m3 is the minimum value of the number of particles, MIN(m1, m2) is the smaller value between m1 and m2. The number of particles corresponding to the reference line calculated in this way can further determine the height position of the reference line. The reference line determined in this way comprehensively refers to the actual particle conditions of the left boundary, the right boundary, and the middle channel, so that the determined reference line can be at a more reasonable height to adapt to different blood samples and has a certain stability. In other embodiments, the setting of the reference line can be adjusted according to the actual situation, which will not be specifically described here.

[0127] S98: Subtract the height of the particle characteristic distribution histogram from the height of the reference line to obtain the corresponding flipped histogram.

[0128] Among them, for the area outside the particle intersection region, the height of the flipped histogram is determined to be 0. For the area within the particle intersection region, the height of the flipped histogram is determined to be the height of the reference line F minus the height of the particle characteristic distribution histogram, that is, the height difference between the reference line F and the corresponding volume / particle number curve.

[0129] In this embodiment, the flipped histogram mainly corresponds to the particle intersection region. The height of the particle characteristic distribution histogram is the height corresponding to multiple volume channels within the particle intersection region. In each volume channel of the particle intersection region, there is the same or different height difference between the reference line F and the corresponding volume / particle number curve. The height difference of different channels is the height value of the corresponding channel in the flipped histogram. Therefore, subtracting the height of the particle characteristic histogram from the height of the reference line F can obtain the corresponding flipped histogram. The flipped histogram is specifically as Figure 12 shown. The particle population represented in the flipped histogram is the flipped particle population.

[0130] S99: Determine the boundary of the particle population according to the flipped histogram to distinguish the particle populations.

[0131] Optionally, the boundary of the particle population can be calculated using the following formula:

[0132]

[0133] where M k is the boundary of the particle population, that is, the boundary between the two populations of platelets and red blood cells, corresponding to a certain volume channel; i is the channel value in the flipped histogram, corresponding to the volume size of the particles, f(i) is the value of the flipped histogram in the i-th channel, g(·) is a processing function, and satisfies: g(x)≥g(y)≥0.

[0134] The principle of the above formula has been described in the previous embodiment. It can be known that through this formula, the boundary of the particle population can be accurately determined and used to distinguish platelets and red blood cells. The rest will not be elaborated here and should also be understood by those skilled in the art.

[0135] Moreover, in this embodiment, since the number of particles corresponding to the reference line in the particle characteristic distribution histogram is not less than the number of particles corresponding to the middle channel, this method in this embodiment has a certain adaptability and can adapt to different blood samples. Especially when dealing with abnormal blood samples with low concentrations, it can be well solved.

[0136] For example, when the upper limit of the platelet volume and the lower limit of the red blood cell volume of a sample are quite close, the determination of the particle intersection region and the reference line becomes particularly important at this time. If the range of the intersection region is too large or too small, it may lead to a large error when calculating the demarcation line, resulting in a poor result in distinguishing particle communities. However, the method of this embodiment can reasonably avoid such errors by using some rules and improve the accuracy of the demarcation line.

[0137] Regarding the determination of the reference line, if the height of the reference line is set too low, it will ultimately lead to poor accuracy of the demarcation line calculated by the preset formula in the flipped histogram. However, the method of this embodiment sets the height of the reference line to be not lower than the number of particles corresponding to the middle channel, and can even be much larger than the middle channel, the left boundary channel or the right boundary channel, thereby improving the accuracy rate. The specific introduction has been made in the foregoing embodiments and will not be elaborated here.

[0138] It should be noted that this embodiment does not limit the upper limit of the height of the reference line. In some embodiments, the specific setting of the reference line may not be limited to the above situation. On the premise of ensuring the calculation accuracy, the height of the reference line can be, for example, N times the height corresponding to the middle channel, where the value of N can be set according to the upper and lower limits of the volume of different particle communities, or can also be set according to the highest point and the lowest point of the channels corresponding to the particle intersection region, so that the reference line obtained according to the reasonable setting method can adapt to various different blood samples, has a certain stability, and accurately calculates the demarcation line based on the preset formula.

[0139] Refer to Figure 13 , Figure 13 is a schematic structural diagram of an embodiment of a particle analysis device provided by the present application. The particle analysis device 130 of this embodiment includes a processor 131 and a memory 132. The processor 131 is coupled to the memory 132. Among them, the memory 132 is used to store a computer program executed by the processor 131, and the processor 131 is used to execute the computer program to implement the following method steps:

[0140] Obtain a particle characteristic distribution histogram; wherein, the first direction coordinate of the particle characteristic distribution histogram is the channel representing the particle characteristics, and the second direction coordinate of the particle characteristic distribution histogram is the number of particles; determine the particle intersection region in the particle characteristic distribution histogram; determine the reference line located in the intersection region; wherein, the reference line is parallel to the first direction; generate a corresponding flipped histogram according to the particle characteristic distribution histogram and the reference line; determine the demarcation line of the particle community according to the flipped histogram to distinguish the particle community.

[0141] Refer to Figure 14 , Figure 14It is a schematic structural diagram of an embodiment of the computer-readable storage medium provided by the present application. The computer-readable storage medium 140 of this embodiment is used to store a computer program 141, and when the computer program 141 is executed by a processor, it is used to implement the following method steps:

[0142] Obtain a particle characteristic distribution histogram; wherein, the first direction coordinate of the particle characteristic distribution histogram is the channel representing the particle characteristics, and the second direction coordinate of the particle characteristic distribution histogram is the particle number; determine the particle intersection region in the particle characteristic distribution histogram; determine the reference line located in the intersection region; wherein, the reference line is parallel to the first direction; generate a corresponding flipped histogram according to the particle characteristic distribution histogram and the reference line; determine the boundary line of the particle community according to the flipped histogram to distinguish the particle community.

[0143] It should be noted that the method steps executed by the computer program 141 of this embodiment are based on the above method embodiment, and its implementation principle and steps are similar. Therefore, when the computer program 141 is executed by a processor, it can also implement the other method steps in any of the above embodiments, which will not be elaborated here.

[0144] When the embodiments of the present application are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0145] The above are only the embodiments of the present application, and do not limit the patent scope of the present application. Any equivalent structural or equivalent process transformation made according to the content of the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present application.

Claims

1. A method for distinguishing particle communities, characterized in that, The method includes: Obtain a particle characteristic distribution histogram; wherein, the first direction coordinate of the particle characteristic distribution histogram is a channel representing particle characteristics, and the second direction coordinate of the particle characteristic distribution histogram is the number of particles; Determine a particle intersection region in the particle characteristic distribution histogram; Determine a reference line located within the intersection region; wherein, the reference line extends along the first direction; Generate a corresponding flipped histogram according to the particle characteristic distribution histogram and the reference line; Determine the boundary line of the particle community according to the flipped histogram to distinguish the particle communities.

2. The method according to claim 1, wherein The determining a particle intersection region in the particle characteristic distribution histogram includes: Determine a left boundary in the particle characteristic distribution histogram; and Determine a right boundary in the particle characteristic distribution histogram; Determine the particle intersection region based on the left boundary and the right boundary.

3. The method according to claim 2, wherein The determining a left boundary in the particle characteristic distribution histogram includes: Determine a preset channel range in the particle characteristic distribution histogram; Determine the corresponding left boundary according to the channel corresponding to the maximum value of the number of particles in the preset channel range; or Determine the corresponding left boundary according to any channel within a preset number of particles range on the right side of the maximum value of the number of particles in the preset channel range.

4. The method according to claim 2, wherein The determining a right boundary in the particle characteristic distribution histogram includes: Determine the right boundary at a preset channel interval on the right side of the left boundary.

5. The method according to claim 4, wherein The preset channel interval is positively correlated with the total number of particles within the preset channel range.

6. The method according to claim 2, wherein The number of particles corresponding to the reference line is not less than the number of particles corresponding to the right boundary; or The number of particles corresponding to the reference line is not less than the number of particles corresponding to any channel within a preset number of particles range on the left side of the right boundary.

7. The method according to claim 1, wherein The generating a corresponding flipped histogram according to the particle characteristic distribution histogram and the reference line includes: Subtract the height of the particle characteristic distribution histogram from the height of the reference line to obtain the corresponding flipped histogram.

8. The method according to claim 1, wherein The determining the boundary line of the particle community according to the flipped histogram to distinguish the particle communities includes: Calculate the boundary line using the following formula: Among them, M k is the boundary line of the particle community, i is the channel value in the flipped histogram, f(i) is the value of the flipped histogram in the i-th channel, g(·) is a processing function, and it satisfies: g(x)≥g(y)≥0.

9. A particle analysis device, characterized in that, It includes a processor and a memory, wherein the memory is used to store a computer program, and when the computer program is executed by the processor, it is used to implement the method for distinguishing particle communities as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, For storing a computer program, when the computer program is executed by a processor, it is used to implement the method for distinguishing particle communities as described in any one of claims 1-8.

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