CN111105407B

CN111105407B - Pathological section dyeing quality evaluation method, device, equipment and storage medium

Info

Publication number: CN111105407B
Application number: CN201911354095.6A
Authority: CN
Inventors: 车拴龙; 罗丕福; 钟学军; 徐炜; 苏丽珠; 林万里; 陈蝶; 丁向东
Original assignee: Guangzhou Kingmed Diagnostics Central Co Ltd
Current assignee: Guangzhou Kingmed Diagnostics Central Co Ltd
Priority date: 2019-12-25
Filing date: 2019-12-25
Publication date: 2023-08-25
Anticipated expiration: 2039-12-25
Also published as: CN111105407A

Abstract

The embodiment of the invention discloses a pathological section dyeing quality evaluation method, a pathological section dyeing quality evaluation device, pathological section dyeing quality evaluation equipment and a storage medium. The method comprises the following steps: digitally scanning the dyed pathological section to obtain a medical image to be analyzed; performing feature recognition on the medical image to be analyzed to obtain a plurality of dyeing color values; and obtaining a dyeing standard value, and determining the dyeing quality of the pathological section corresponding to the medical image to be analyzed according to the plurality of dyeing color values and the dyeing standard value. The invention has unified evaluation standard, adopts artificial intelligence to avoid subjective evaluation of pathologists or pathologists, ensures consistency of quality evaluation, is suitable for pathological section dyeing quality evaluation in the same laboratory, and is also suitable for pathological section dyeing quality evaluation among different laboratories.

Description

Pathological section dyeing quality evaluation method, device, equipment and storage medium

Technical Field

The invention relates to the technical field of quality evaluation, in particular to a pathological section dyeing quality evaluation method, device and equipment and a storage medium.

Background

The pathological technology is an important branch of pathology, is a methodology in pathological research, and is the basis of pathological diagnosis. Conventional pathology is the most important part of pathological technology, and any pathological diagnosis is not separated. Immunohistochemical staining is an important technology indispensable to modern pathological diagnosis technology. The steps of immunohistochemical staining are cumbersome and may lead to complete inadequacy of the final immunohistochemical staining effect due to different laboratory and technician handling techniques. In the same laboratory, 3 laboratory operators operate at different times to dye with three different effects, and the result of the later pathological diagnosis report can be seriously influenced.

Currently, subjective evaluations are often performed by pathologists or pathologists for quality control, both in the same laboratory and between different laboratories. On the one hand, the standard of diagnosis quality is not completely consistent among everyone, and most of the individuals are subjective and difficult to evaluate repeatedly; on the other hand, with respect to the fine quality difference, the evaluation results of the people tend to be more different, and reliable and accurate evaluation cannot be completed. The quality control evaluation criteria and results are very unstable at each time, thus making consistent quality of immunohistochemical staining difficult to achieve in different laboratories. Therefore, it is important to develop a method for evaluating the quality of pathological section staining, which has uniform detection standard and is suitable for the same laboratory and different laboratories.

Disclosure of Invention

In view of the above, it is necessary to provide a pathological section dyeing quality evaluation method, apparatus, device and storage medium.

In a first aspect, the invention provides a pathological section staining quality evaluation method, which comprises the following steps:

digitally scanning the dyed pathological section to obtain a medical image to be analyzed;

performing feature recognition on the medical image to be analyzed to obtain a plurality of dyeing color values;

and obtaining a dyeing standard value, and determining the dyeing quality of the pathological section corresponding to the medical image to be analyzed according to the plurality of dyeing color values and the dyeing standard value.

In a second aspect, the present invention also provides a pathological section dyeing quality evaluation device, which includes:

the scanning module is used for digitally scanning the dyed pathological section to obtain a medical image to be analyzed;

the dyeing color value extraction module is used for carrying out feature recognition on the medical image to be analyzed to obtain a plurality of dyeing color values;

and the dyeing quality determining module is used for obtaining a dyeing standard value and determining the dyeing quality of the pathological section corresponding to the medical image to be analyzed according to the plurality of dyeing color values and the dyeing standard value.

In a third aspect, the invention also proposes a storage medium storing a program of computer instructions which, when executed by a processor, cause the processor to perform the steps of the method of any of the first aspects.

In a fourth aspect, the present invention also proposes a computer device comprising at least one memory, at least one processor, the memory storing a program of computer instructions which, when executed by the processor, cause the processor to perform the steps of the method of any of the first aspects.

In conclusion, according to the pathological section dyeing quality evaluation method disclosed by the invention, the dyed pathological section is digitally scanned to obtain the medical image to be analyzed, and the digital medical image to be analyzed is analyzed through artificial intelligence, so that subjective evaluation of a pathologist or a pathologist is avoided, and consistency of quality evaluation is ensured; the method comprises the steps of performing feature recognition on a medical image to be analyzed to obtain a plurality of dyeing color values, obtaining a dyeing standard value, determining the dyeing quality of a pathological section corresponding to the medical image to be analyzed according to the plurality of dyeing color values and the dyeing standard value, wherein the method for recognizing the dyeing color values is the same, evaluating the pathological section by adopting the plurality of dyeing color values and the dyeing standard value, and the method is uniform in evaluation parameters and evaluation standard, and adopts artificial intelligence, so that the method is suitable for evaluating the dyeing quality of the pathological section in the same laboratory and is also suitable for evaluating the dyeing quality of the pathological section among different laboratories. Therefore, the evaluation standard of the invention is unified, subjective evaluation of pathologists or pathologists is avoided by adopting artificial intelligence, consistency of quality evaluation is ensured, and the invention is suitable for pathological section dyeing quality evaluation in the same laboratory and pathological section dyeing quality evaluation among different laboratories.

Drawings

In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Wherein:

FIG. 1 is a flow chart of a method for evaluating the staining quality of a pathological section in one embodiment;

FIG. 2 is a flowchart of the identification staining color value of the pathological section staining quality evaluation method of FIG. 1;

FIG. 3 is a flow chart of cell structure feature recognition of the pathological section staining quality evaluation method of FIG. 1;

FIG. 4 is a flowchart of the method for evaluating the staining quality of the pathological section of FIG. 1;

FIG. 5 is a flowchart of the method for evaluating the quality of staining of the pathological section of FIG. 1;

FIG. 6 is a flowchart of the method for evaluating the quality of staining of the pathological section of FIG. 1 for calculating the difference of staining colors;

FIG. 7 is a flowchart of a method for evaluating the staining quality of a pathological section according to another embodiment;

FIG. 8 is a flowchart of the pathological section dyeing quality evaluation method of FIG. 1 for analyzing reasons of failure;

FIG. 9 is a block diagram showing a structure of a pathological section staining quality evaluation apparatus according to an embodiment;

FIG. 10 is a block diagram of a computer device in one embodiment.

Detailed Description

The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

As shown in fig. 1, in one embodiment, a pathological section staining quality evaluation method is provided, which includes:

s102, digitally scanning the dyed pathological section to obtain a medical image to be analyzed;

the pathological section is prepared by taking pathological tissue with a certain size, preparing the pathological section by using a pathological histology method, and further checking the pathological section by using a microscope.

Traditional staining of pathological sections includes: HE staining, bus staining, jemsa staining, collagen fiber staining (Masson et al), reticular fiber staining, elastane staining (hematoxylin phosphotungstic acid), fat staining (sudan III), glycogen staining (PAS), mucus staining (PAS), etc., and immunochemical staining of pathological sections includes: immunohistochemical staining (immunohistochemistry), immunofluorescent staining, and the like, are not particularly limited herein as examples. The application is illustrated as applied to immunohistochemistry, it being understood that the method of the application is equally applicable to traditional staining of pathological sections and other immunochemical staining.

The digital scanning refers to digital scanning of the dyed pathological section to obtain a digital initial medical image. The digitized scan may be implemented using a digital camera or a scanner, for example and without limitation.

The initial medical image may be directly used as the medical image to be analyzed, or an image obtained by correcting the initial medical image may be used as the medical image to be analyzed.

S104, performing feature recognition on the medical image to be analyzed to obtain a plurality of dyeing color values;

performing cell structure feature recognition according to the medical image to be analyzed to obtain a cell nucleus image and a cell plasma image; and respectively performing color value calculation according to the cell nucleus image and the cell plasma image to obtain a plurality of dyeing color values.

It is understood that the plurality of the staining color values may include a nuclear negative staining color value, a cytoplasmic negative staining color value, a nuclear positive staining color value, a nuclear negative staining color value, a cytoplasmic positive staining color value, and a nuclear negative staining color value, a cytoplasmic negative staining color value, a nuclear positive staining color value, and a cytoplasmic positive staining color value.

Optionally, the color values refer to the values of three red (R), green (G), and blue (B) color channels, which are also called RGB values, denoted (Rx, gx, bx), where Rx is the value of the red channel, gx is the value of the green channel, and Bx is the value of the blue channel, which are not specifically limited herein.

The cell nucleus negative staining color value refers to a color value obtained by staining cell nucleus negative.

The cytoplasmic negative staining color value refers to a color value obtained by staining cytoplasmic negative.

The color value of the positive staining of the cell nucleus refers to the color value obtained by staining the positive staining of the cell nucleus.

The color value of the positive staining of the cell plasma refers to the color value obtained by positively staining the cell plasma.

The cell nucleus refers to the largest and most important cell structure in eukaryotic cells, is a control center of cytogenetic and metabolism, and is one of the most obvious marks of eukaryotic cells, which are different from prokaryotic cells.

The cytoplasm refers to cytoplasm and is the collective term for all semitransparent, gelatinous and granular substances except for nuclear areas surrounded by cytoplasmic membranes.

S106, obtaining a dyeing standard value, and determining the dyeing quality of the pathological section corresponding to the medical image to be analyzed according to the plurality of dyeing color values and the dyeing standard value.

Alternatively, the dyeing standard value may be a specific RGB value or a range value.

Optionally, scoring the dyeing color value and a dyeing standard value corresponding to the dyeing color value to obtain a dyeing color value score, comprehensively scoring according to all the dyeing color value scores to obtain a pathological section dyeing comprehensive score, obtaining a dyeing comprehensive score standard value, and comparing and determining the dyeing quality of the pathological section corresponding to the medical image to be analyzed according to the dyeing comprehensive score standard value and the pathological section dyeing comprehensive score.

Optionally, the evaluation result of the dyeing color value is qualified when the dyeing color value is within the range of the dyeing standard value corresponding to the dyeing color value, and the evaluation result of the dyeing color value is unqualified when the dyeing color value is outside the range of the dyeing standard value corresponding to the dyeing color value; and comprehensively evaluating according to all the evaluation results of the dyeing color values to obtain the dyeing quality of the pathological section corresponding to the medical image to be analyzed.

The comprehensive evaluation is carried out according to all the evaluation results of the dyeing color values to obtain the dyeing quality of the pathological section corresponding to the medical image to be analyzed, and the method comprises the following steps: when all the dyeing color value evaluation results are qualified, the dyeing quality of the pathological section corresponding to the medical image to be analyzed is qualified, and when all the dyeing color value evaluation results are partially unqualified, the dyeing quality of the pathological section corresponding to the medical image to be analyzed is unqualified; it will be appreciated that other methods of comprehensive evaluation are also possible, and the examples herein are not specifically limited.

The dyeing standard value is a pathological section with the best dyeing quality evaluated by an expert pathologist, and the color value obtained by digitally scanning according to the pathological section is a reference standard which can be used for evaluating the dyeing quality and is obtained through repeated experiments.

It is understood that the number of the dyeing standard values is plural, and the dyeing standard values are in one-to-one correspondence with the dyeing color values. For example, the cell nucleus negative staining color value corresponds to a staining standard value, the cell plasma negative staining color value corresponds to a staining standard value, the cell nucleus positive staining color value corresponds to a staining standard value, and the cell plasma positive staining color value corresponds to a staining standard value, which is not particularly limited herein.

Optionally, the staining standard value includes: a nuclear negative staining standard value corresponding to a nuclear negative staining color value, a cytoplasmic negative staining standard value corresponding to a cytoplasmic negative staining color value, a nuclear positive staining standard value corresponding to a nuclear positive staining color value, and a cytoplasmic positive staining standard value corresponding to a cytoplasmic positive staining color value.

Alternatively, the one-to-one correspondence may refer to that the dyeing standard value and the dyeing color value corresponding to the dyeing standard value adopt the same dyeing method, or may refer to that the dyeing standard value and the dyeing color value corresponding to the dyeing standard value adopt the same organ tissue and the same dyeing method, or may refer to that the dyeing standard value and the dyeing color value corresponding to the dyeing standard value adopt the same organ tissue, the same dyeing method and the same pathology, which are not limited in particular herein.

Optionally, the stained pathological section refers to a pathological section that completes all staining phases, and the staining standard value is also a staining standard value corresponding to a pathological section that completes all staining phases.

Optionally, the staining includes a plurality of staining stages, and if one of the stained pathological sections is a pathological section after the staining stage, the staining standard value is also a staining standard value corresponding to the pathological section after the staining stage. The dyeing quality evaluation of the pathological section by adopting staged dyeing can rapidly locate the dyeing stage of the unqualified dyed pathological section, and is convenient for the subsequent timely solution of the corresponding problem.

According to the pathological section dyeing quality evaluation method, the dyed pathological section is digitally scanned to obtain the medical image to be analyzed, and the digital medical image to be analyzed is analyzed through artificial intelligence, so that subjective evaluation of a pathologist or a pathologist is avoided, and consistency of quality evaluation is ensured; the method comprises the steps of performing feature recognition on a medical image to be analyzed to obtain a plurality of dyeing color values, obtaining a dyeing standard value, determining the dyeing quality of a pathological section corresponding to the medical image to be analyzed according to the plurality of dyeing color values and the dyeing standard value, wherein the method for recognizing the dyeing color values is the same, evaluating the pathological section by adopting the plurality of dyeing color values and the dyeing standard value, and the method is uniform in evaluation parameters and evaluation standard, and adopts artificial intelligence, so that the method is suitable for evaluating the dyeing quality of the pathological section in the same laboratory and is also suitable for evaluating the dyeing quality of the pathological section among different laboratories.

As shown in fig. 2, in one embodiment, the feature recognition is performed on the medical image to be analyzed to obtain a plurality of color values, including:

s202, recognizing cell structural features according to the medical image to be analyzed to obtain a cell nucleus image and a cell plasma image;

the cell nucleus segmentation algorithm and the cell plasma segmentation algorithm can be selected from the prior art to respectively perform feature recognition on the cell structure in the medical image to be analyzed, so as to obtain a cell nucleus image and a cell plasma image. It will be appreciated that other algorithms may be used to identify the characteristics of the cellular structure in the medical image to be analyzed, and the examples are not limited in detail herein.

S204, calculating color values according to the cell nucleus image and the cell plasma image respectively to obtain a plurality of dyeing color values, wherein the dyeing color values comprise cell nucleus negative dyeing color values, cell plasma negative dyeing color values, cell nucleus positive dyeing color values and/or cell plasma positive dyeing color values.

As shown in fig. 3, in one embodiment, the identifying the cell structural feature according to the medical image to be analyzed to obtain a nuclear image and a cytoplasmic image includes:

S302, dividing cell nuclei by a cell nucleus segmentation algorithm according to the medical image to be analyzed to obtain a cell nucleus image;

specifically, according to the medical image to be analyzed, a cell nucleus is segmented by a cell nucleus segmentation algorithm, so that a cell nucleus image is obtained, and the number of the cell nucleus images is multiple. The cell nucleus segmentation algorithm may be selected from the prior art and will not be described in detail herein.

S304, dividing the cytoplasm according to the medical image to be analyzed by adopting a cytoplasm dividing algorithm to obtain a cytoplasm image.

Specifically, a cytoplasm segmentation algorithm is adopted to segment cytoplasm according to the medical image to be analyzed, so as to obtain cytoplasm images, wherein the number of the cytoplasm images is a plurality of. The cytoplasmic segmentation algorithm may be selected from the prior art and will not be described in detail herein.

As shown in fig. 4, in one embodiment, the calculating color values according to the nucleus image and the cytoplasm image respectively, to obtain a plurality of dyeing color values, where the plurality of dyeing color values includes a nucleus negative dyeing color value, a cytoplasm negative dyeing color value, a nucleus positive dyeing color value and/or a cytoplasm positive dyeing color value, includes:

S402, classifying according to the color values of the cell nucleus images to obtain cell nucleus negative staining images and cell nucleus positive staining images;

specifically, the color value of the cell nucleus image is a positive staining image of cell nucleus, and the color value of the cell nucleus image is a negative staining image of cell nucleus. For example, in immunohistochemistry, the cell nucleus positive staining is black brown, and the cell nucleus negative staining is blue, and the examples are not particularly limited.

S404, classifying according to the color value of the cytoplasmic image to obtain a cytoplasmic negative staining image and a cytoplasmic positive staining image;

specifically, the color value of the cytoplasmic image is a positive staining image of the cytoplasm, and the color value of the cytoplasmic image is a negative staining image of the cytoplasm.

S406, calculating color values according to the cell nucleus negative staining image, the cell nucleus positive staining image, the cell plasma negative staining image and the cell plasma positive staining image respectively to obtain a cell nucleus negative staining color value, a cell plasma negative staining color value, a cell nucleus positive staining color value and a cell plasma positive staining color value.

Specifically, calculating a color value according to the cell nucleus negative staining image to obtain a cell nucleus negative staining color value; calculating a color value according to the cell nucleus positive staining image to obtain a cell nucleus positive staining color value; calculating a color value according to the cytoplasmic negative staining image to obtain a cytoplasmic negative staining color value; and respectively calculating the color values according to the cell plasma positive staining images to obtain the cell plasma positive staining color values.

The color value calculation can calculate the average value of RGB of all pixel points in the dyed image, can extract the maximum value of RGB of all pixel points in the dyed image, and can also extract the minimum value of RGB of all pixel points in the dyed image; it will be appreciated that other algorithms may be used for the color value calculation, and the examples are not specifically limited herein.

Optionally, the dyeing color value and the dyeing standard value corresponding to the dyeing color value adopt the same color value calculation method, so that the accuracy and consistency of dyeing quality evaluation are improved.

As shown in fig. 5, in one embodiment, the determining the staining quality of the pathological section corresponding to the medical image to be analyzed according to the plurality of staining color values and the staining standard value includes:

S502, scoring the dyeing color value and a dyeing standard value corresponding to the dyeing color value to obtain a dyeing color value score;

when the dyeing standard value is a specific RGB value, calculating the dyeing color value and a difference value before the dyeing standard value corresponding to the dyeing color value to obtain a dyeing color difference value, and grading according to the dyeing color difference value to obtain a dyeing color value grading; and when the dyeing standard value is a range value, the dyeing color value score is full when the dyeing color value is within the range value of the dyeing standard value corresponding to the dyeing color value, and when the dyeing color value is not within the range value of the dyeing standard value corresponding to the dyeing color value, the dyeing color value score is calculated according to a preset scoring rule.

And calculating according to a preset scoring rule to obtain a scoring of the dyeing color value when the dyeing color value is not in the range value of the dyeing standard value corresponding to the dyeing color value, wherein the scoring comprises the following steps: calculating the average value of the range value starting point and the end point of the range value of the dyeing standard value corresponding to the dyeing color value to obtain a dyeing standard value center; when the dyeing color value is smaller than the center of the dyeing standard value, subtracting the dyeing color value from the range value starting point of the range value of the dyeing standard value corresponding to the dyeing color value to obtain a deviation difference value; and when the dyeing color value is larger than the dyeing standard value center, subtracting the range value end point of the range value of the dyeing standard value corresponding to the dyeing color value from the dyeing color value to obtain a deviation difference value, and calculating according to the deviation difference value to obtain a dyeing color value score.

The calculating to obtain the dyeing color value score according to the deviation difference value comprises the following steps: and multiplying the deviation difference value by a preset coefficient to obtain a deviation score, and subtracting the deviation score from the full score to obtain a dyeing color value score. It will be appreciated that other algorithms may be used to calculate the staining color value score, the examples are not specifically limited herein.

S504, comprehensively scoring according to all the staining color value scores to obtain pathological section staining comprehensive scores;

and carrying out weighted summation on all the staining color value scores to obtain a pathological section staining comprehensive score. It will be appreciated that other algorithms may be used for the composite score, and the examples are not specifically limited herein.

Optionally, when the scores of all the dyeing color values are weighted and summed, the weights may be set for the dyeing color values according to pathology, the weights may be set for the dyeing color values according to a dyeing method, and the weights may be set for the dyeing color values according to pathology and a dyeing method, which is not limited specifically herein.

S506, obtaining a comprehensive dyeing score standard value, and comparing and determining the dyeing quality of the pathological section corresponding to the medical image to be analyzed according to the comprehensive dyeing score standard value and the comprehensive pathological section dyeing score.

Alternatively, the dyeing synthesis score standard value may be a specific RGB value or a range value.

When the comprehensive dyeing score standard value is a specific RGB value, the dyeing quality of the pathological section corresponding to the medical image to be analyzed is qualified when the comprehensive dyeing score of the pathological section is larger than or equal to the comprehensive dyeing score standard value, and the dyeing quality of the pathological section corresponding to the medical image to be analyzed is unqualified when the comprehensive dyeing score of the pathological section is smaller than the comprehensive dyeing score standard value; and when the comprehensive dyeing score standard value is a range value, the comprehensive dyeing score of the pathological section is within the range value of the comprehensive dyeing score standard value, the dyeing quality of the pathological section corresponding to the medical image to be analyzed is qualified, and when the comprehensive dyeing score of the pathological section is outside the range value of the comprehensive dyeing score standard value, the dyeing quality of the pathological section corresponding to the medical image to be analyzed is unqualified.

Optionally, the weight of each dyeing comprehensive score standard value may be set according to a pathology, may be set according to a dyeing method, and may be set according to a pathology and a dyeing method, which is not specifically limited herein.

According to the embodiment, the objectivity evaluation system and the index are established, so that the accuracy and objectivity of the pathological section dyeing quality evaluation are improved, the fact that each evaluation depends on a professional pathologist is not needed, the labor cost for evaluating the dyeing quality is reduced, the subjective influence of different pathologists on the accuracy of the evaluation can be avoided, the uniform evaluation system is convenient to use in the same laboratory and among different laboratories, and the consistency of quality evaluation is ensured.

In one embodiment, the scoring the dyeing color value and the dyeing standard value corresponding to the dyeing color value to obtain a dyeing color value score includes: calculating the dyeing color value and a difference value before a dyeing standard value corresponding to the dyeing color value to obtain a dyeing color difference value; and scoring according to the dyeing color difference value to obtain a dyeing color value score.

As shown in fig. 6, in one embodiment, the dyeing color values include channel values for three channels, and the dyeing standard values include channel standard values for three channels;

the calculating the difference between the dyeing color value and the dyeing standard value corresponding to the dyeing color value to obtain a dyeing color difference value comprises the following steps:

S602, respectively calculating a channel difference value between the channel value of each channel and a channel standard value corresponding to the channel value;

for example, when RGB is adopted as the color value, the channel value of the R channel of the color value is subtracted from the channel value of the R channel of the color standard value corresponding to the color value to obtain an R channel difference value, the channel value of the G channel of the color value is subtracted from the channel value of the G channel of the color standard value corresponding to the color value to obtain a G channel difference value, and the channel value of the B channel of the color value is subtracted from the channel value of the B channel of the color standard value corresponding to the color value to obtain a B channel difference value, which is not specifically limited herein.

S604, calculating an absolute value according to the channel difference value to obtain a channel color difference value;

for example, when the color value adopts RGB, calculating the absolute value of the R channel difference value to obtain the R channel color difference value, calculating the absolute value of the G channel difference value to obtain the G channel color difference value, and calculating the absolute value of the B channel difference value to obtain the B channel color difference value, wherein the R channel color difference value, the G channel color difference value, and the B channel color difference value are used as the channel color difference values.

And S606, carrying out weighted summation calculation according to the three channel color difference values to obtain a dyeing color difference value.

For example, when the color value adopts RGB, the R channel color difference value, the G channel color difference value, and the B channel color difference value are weighted and summed to obtain the dyeing color difference value.

Alternatively, the weight of each channel color difference may be set according to a pathology, a dyeing method, or a pathology and a dyeing method, which is not specifically limited herein.

In one embodiment, the scoring according to the dyeing color difference value to obtain a dyeing color value score includes: dividing the dyeing color difference value by a preset numerical value to obtain a dyeing color value score. It will be appreciated that other algorithms may be selected, such as, for example, scoring the color difference directly as a color value, or dividing the color difference by 255 to obtain a difference index and subtracting 1 from the difference index to obtain a color value score, as examples and not specifically limited herein.

As shown in fig. 7, in one embodiment, a method for evaluating the staining quality of a pathological section is also provided, the method comprising:

s702, digitally scanning the dyed pathological section to obtain an initial medical image;

Specifically, the stained pathological section is digitally scanned to obtain a digitized initial medical image.

S704, performing binarization processing on the initial medical image to obtain a binarized medical image;

specifically, an image binarization algorithm is adopted for the initial medical image, and a binarized medical image is obtained.

Image binarization (Image Binarization) is a process of setting the gray value of a pixel point on an image to 0 or 255, that is, displaying a clear black-and-white effect on the whole image.

S706, acquiring a color value with the lowest numerical value from the binarized medical image to obtain a binarized lowest color value;

s708, determining a lowest color value of the initial medical image corresponding to the binary lowest color value according to the binary lowest color value;

specifically, the position of the corresponding pixel point is determined according to the binarized minimum color value, and the color value before the pixel point of the position is not binarized is used as the minimum color value of the initial medical image corresponding to the binarized minimum color value.

S710, correcting the initial medical image according to the minimum color value of the initial medical image corresponding to the binarized minimum color value to obtain the medical image to be analyzed;

Optionally, calculating a corrected color value according to the color value of the white and the lowest color value of the initial medical image corresponding to the binarized lowest color value; and obtaining the medical image to be analyzed according to the initial medical image and the corrected color value.

For example, when RGB is adopted as the color value, subtracting the channel value of the R channel of the lowest color value of the initial medical image corresponding to the binary lowest color value from 255 to obtain a corrected color value of the R channel, subtracting the channel value of the G channel of the lowest color value of the initial medical image corresponding to the binary lowest color value from 255 to obtain a corrected color value of the G channel, and subtracting the channel value of the B channel of the lowest color value of the initial medical image corresponding to the binary lowest color value from 255 to obtain a corrected color value of the B channel; subtracting the corrected color value of the R channel from the channel value of the R channel of all the pixels of the initial medical image, subtracting the corrected color value of the G channel from the channel value of the G channel of all the pixels of the initial medical image, subtracting the corrected color value of the B channel from the channel value of the B channel of all the pixels of the initial medical image, and completing the subtracted initial medical image as the medical image to be analyzed, which is not particularly limited herein by way of example.

The lowest color value of the initial medical image corresponding to the binarized lowest color value is a background color, the background color is normally white, the RGB color value of the white is (255 ), and when the digital scanning is performed, the illumination is different, and the background color becomes other colors.

S712, performing feature recognition on the medical image to be analyzed to obtain a plurality of dyeing color values;

s714, obtaining a dyeing standard value, and determining the dyeing quality of the pathological section corresponding to the medical image to be analyzed according to the plurality of dyeing color values and the dyeing standard value.

According to the embodiment, the medical image to be analyzed is obtained by correcting the initial medical image, and then the medical image to be analyzed is subjected to dyeing quality evaluation, so that chromatic aberration caused by illumination during digital scanning is avoided, and the accuracy of pathological section dyeing quality evaluation is further improved.

In one embodiment, after determining the staining quality of the pathological section corresponding to the medical image to be analyzed according to the plurality of staining color values and the staining standard value, the method further comprises: acquiring an evaluation information table, wherein the evaluation information table comprises laboratory marks, dyeing person marks and dyeing process data corresponding to dyed pathological sections; updating the evaluation information table, the medical image to be analyzed, a plurality of dyeing color values, the dyeing standard values and the dyeing quality of pathological sections corresponding to the medical image to be analyzed to a pathological section dyeing database. Specifically, an evaluation information table input by a user is acquired, and then the evaluation information table corresponding to the dyed pathological section, the medical image to be analyzed, a plurality of dyeing color values, the dyeing standard value and the dyeing quality of the pathological section corresponding to the medical image to be analyzed are added into the pathological section dyeing database.

The user may be a pathologist, and the examples are not specifically limited herein.

The staining process data includes reagent-added data including reagent name, time, and measurement, antibody-added data including antibody name, time, and measurement, and incubation conditions, and examples are not specifically limited.

The dyeing person identifier is used to uniquely identify a dyeing technician, and may be a name, an ID, etc., and is not specifically limited herein.

As shown in fig. 8, in one embodiment, the method further comprises:

s802, acquiring the laboratory identification;

the laboratory identifier is used to uniquely identify a laboratory, and may be a laboratory name or a laboratory ID number, which is not specifically limited herein.

S804, acquiring the evaluation information table, the medical image to be analyzed, a plurality of dyeing color values and the dyeing standard values corresponding to unqualified dyeing quality of the pathological section from a pathological section dyeing database according to the laboratory mark;

s806, performing unqualified reason analysis according to the evaluation information table, the medical image to be analyzed, the plurality of dyeing color values and the dyeing standard value, and obtaining unqualified reason data.

The failure cause analysis includes a reagent addition amount, a reagent addition time, a reagent addition sequence, an antibody addition amount, an antibody addition time, and an antibody addition sequence, and the examples are not particularly limited.

In one embodiment, after performing the failure cause analysis according to the evaluation information table, the medical image to be analyzed, the plurality of dyeing color values, and the dyeing standard value, obtaining failure cause data, the method further includes: acquiring an improvement suggestion list; and acquiring an improvement suggestion from the improvement suggestion list according to the unqualified reason data, and obtaining a laboratory improvement suggestion list. And specifically, searching and finding the unqualified reason data from the improvement suggestion list, and matching to obtain a laboratory improvement suggestion list.

The improvement suggestion list is a reconstruction library established by expert pathologists after comprehensive evaluation from a plurality of stained pathological sections.

The embodiment obtains a laboratory improvement suggestion list through data analysis, and is beneficial to improving the operation standard, the test standard and the training system of a laboratory according to the laboratory improvement suggestion list.

As shown in fig. 9, in one embodiment, there is also provided a pathological section staining quality evaluation apparatus, the apparatus comprising:

The scanning module 902 is used for digitally scanning the dyed pathological section to obtain a medical image to be analyzed;

the dyeing color value extraction module 904 is configured to perform feature recognition on the medical image to be analyzed to obtain a plurality of dyeing color values;

the staining quality determining module 906 is configured to obtain a staining standard value, and determine a staining quality of the pathological section corresponding to the medical image to be analyzed according to the plurality of staining color values and the staining standard value.

The pathological section dyeing quality evaluation device of the embodiment performs digital scanning on the dyed pathological section to obtain a medical image to be analyzed, and analyzes the digital medical image to be analyzed through artificial intelligence, so that subjective evaluation of a pathologist or a pathologist is avoided, and consistency of quality evaluation is ensured; the method comprises the steps of performing feature recognition on a medical image to be analyzed to obtain a plurality of dyeing color values, obtaining a dyeing standard value, determining the dyeing quality of a pathological section corresponding to the medical image to be analyzed according to the plurality of dyeing color values and the dyeing standard value, wherein the method for recognizing the dyeing color values is the same, evaluating the pathological section by adopting the plurality of dyeing color values and the dyeing standard value, and the method is uniform in evaluation parameters and evaluation standard, and adopts artificial intelligence, so that the method is suitable for evaluating the dyeing quality of the pathological section in the same laboratory and is also suitable for evaluating the dyeing quality of the pathological section among different laboratories.

In one embodiment, the scanning module 902 includes a digitized scanning sub-module, a color correction sub-module;

the digital scanning sub-module is used for digitally scanning the dyed pathological section to obtain an initial medical image;

the color correction sub-module is used for performing binarization processing on the initial medical image to obtain a binarized medical image, acquiring a color value with the lowest numerical value from the binarized medical image to obtain a binarized minimum color value, determining the minimum color value of the initial medical image corresponding to the binarized minimum color value according to the binarized minimum color value, and performing correction processing on the initial medical image according to the minimum color value of the initial medical image corresponding to the binarized minimum color value to obtain the medical image to be analyzed.

In one embodiment, the apparatus further comprises:

the data updating module is used for acquiring an evaluation information table, wherein the evaluation information table comprises laboratory identification, dyeing person identification and dyeing process data corresponding to the dyed pathological section, and updating the evaluation information table, the medical image to be analyzed, a plurality of dyeing color values, the dyeing standard value and the dyeing quality of the pathological section corresponding to the medical image to be analyzed to a pathological section dyeing database.

In one embodiment, the apparatus further comprises:

the laboratory quality control module is used for acquiring the laboratory identification, acquiring the evaluation information table, the medical image to be analyzed, a plurality of dyeing color values and the dyeing standard value corresponding to the unqualified dyeing quality of the pathological section from the pathological section dyeing database according to the laboratory identification, and performing unqualified reason analysis according to the evaluation information table, the medical image to be analyzed, the plurality of dyeing color values and the dyeing standard value to obtain unqualified reason data.

FIG. 10 illustrates an internal block diagram of a computer device in one embodiment. The computer device may specifically be a terminal or a server. As shown in fig. 10, the computer device includes a processor, a memory, and a network interface connected by a system bus. The memory includes a nonvolatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system, and may also store a computer program that, when executed by a processor, causes the processor to implement a pathological section staining quality evaluation method. The internal memory may also store a computer program which, when executed by the processor, causes the processor to perform a pathological section staining quality evaluation method. It will be appreciated by those skilled in the art that the structure shown in FIG. 10 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.

In one embodiment, the method for evaluating the staining quality of a pathological section provided by the application can be implemented as a computer program, and the computer program can be run on a computer device as shown in fig. 10. The memory of the computer equipment can store each program template of the pathological section dyeing quality evaluation device. Such as a scanning module 902, a staining color value extraction module 904, a staining quality determination module 906.

In one embodiment, the present application also proposes a storage medium storing a program of computer instructions which, when executed by a processor, cause the processor to perform the method steps of:

The method comprises the steps of digitally scanning the dyed pathological section to obtain a medical image to be analyzed, analyzing the digital medical image to be analyzed through artificial intelligence, avoiding subjective evaluation of a pathologist or a pathologist, and ensuring consistency of quality evaluation; the method comprises the steps of performing feature recognition on a medical image to be analyzed to obtain a plurality of dyeing color values, obtaining a dyeing standard value, determining the dyeing quality of a pathological section corresponding to the medical image to be analyzed according to the plurality of dyeing color values and the dyeing standard value, wherein the method for recognizing the dyeing color values is the same, evaluating the pathological section by adopting the plurality of dyeing color values and the dyeing standard value, and the method is uniform in evaluation parameters and evaluation standard, and adopts artificial intelligence, so that the method is suitable for evaluating the dyeing quality of the pathological section in the same laboratory and is also suitable for evaluating the dyeing quality of the pathological section among different laboratories.

In one embodiment, the feature recognition is performed on the medical image to be analyzed to obtain a plurality of color values, including: performing cell structure feature recognition according to the medical image to be analyzed to obtain a cell nucleus image and a cell plasma image; and respectively calculating color values according to the cell nucleus image and the cell plasma image to obtain a plurality of dyeing color values, wherein the plurality of dyeing color values comprise cell nucleus negative dyeing color values, cell plasma negative dyeing color values, cell nucleus positive dyeing color values and/or cell plasma positive dyeing color values.

In one embodiment, the identifying the cell structure features according to the medical image to be analyzed to obtain a nuclear image and a cytoplasm image includes: dividing cell nuclei by a cell nucleus segmentation algorithm according to the medical image to be analyzed to obtain a cell nucleus image; and dividing the cytoplasm according to the medical image to be analyzed by adopting a cytoplasm dividing algorithm to obtain a cytoplasm image.

In one embodiment, the calculating the color values according to the nucleus image and the cytoplasm image respectively to obtain a plurality of staining color values, where the plurality of staining color values includes a nucleus negative staining color value, a cytoplasm negative staining color value, a nucleus positive staining color value and/or a cytoplasm positive staining color value, includes: classifying according to the color value of the cell nucleus image to obtain a cell nucleus negative staining image and a cell nucleus positive staining image; classifying according to the color value of the cytoplasm image to obtain a cytoplasm negative staining image and a cytoplasm positive staining image; and calculating color values according to the cell nucleus negative staining image, the cell nucleus positive staining image, the cell plasma negative staining image and the cell plasma positive staining image respectively to obtain a cell nucleus negative staining color value, a cell plasma negative staining color value, a cell nucleus positive staining color value and a cell plasma positive staining color value.

In one embodiment, the staining criteria values include: nuclear negative staining standard value, cytoplasmic negative staining standard value, nuclear positive staining standard value, and cytoplasmic positive staining standard value.

In one embodiment, the determining the staining quality of the pathological section corresponding to the medical image to be analyzed according to the plurality of staining color values and the staining standard value includes: scoring the dyeing color value and a dyeing standard value corresponding to the dyeing color value to obtain a dyeing color value score; comprehensively scoring according to all the staining color value scores to obtain pathological section staining comprehensive scores; and obtaining a comprehensive dyeing score standard value, and comparing according to the comprehensive dyeing score standard value and the comprehensive pathological section dyeing score to determine the dyeing quality of the pathological section corresponding to the medical image to be analyzed.

In one embodiment, the staining color value comprises a channel number value for three channels, and the staining standard value comprises a channel standard value for three channels; the calculating the difference between the dyeing color value and the dyeing standard value corresponding to the dyeing color value to obtain a dyeing color difference value comprises the following steps: respectively calculating a channel difference value between the channel value of each channel and a channel standard value corresponding to the channel value; calculating an absolute value according to the channel difference value to obtain a channel color difference value; and carrying out weighted summation calculation according to the three channel color differences to obtain a dyeing color difference.

In one embodiment, the scoring according to the dyeing color difference value to obtain a dyeing color value score includes: dividing the dyeing color difference value by a preset numerical value to obtain a dyeing color value score.

In one embodiment, the digitally scanning the stained pathological section to obtain a medical image to be analyzed includes: digitally scanning the dyed pathological section to obtain an initial medical image; performing binarization processing on the initial medical image to obtain a binarized medical image; acquiring a color value with the lowest numerical value from the binarized medical image to obtain a binarized lowest color value; determining a lowest color value of the initial medical image corresponding to the binarized lowest color value according to the binarized lowest color value; and correcting the initial medical image according to the minimum color value of the initial medical image corresponding to the binarized minimum color value to obtain the medical image to be analyzed.

In one embodiment, the correcting the initial medical image according to the lowest color value of the initial medical image corresponding to the binary lowest color value to obtain the medical image to be analyzed includes:

calculating a corrected color value according to the color value of the white and the lowest color value of the initial medical image corresponding to the binarized lowest color value; and obtaining the medical image to be analyzed according to the initial medical image and the corrected color value.

In one embodiment, after determining the staining quality of the pathological section corresponding to the medical image to be analyzed according to the plurality of staining color values and the staining standard value, the method further comprises: acquiring an evaluation information table, wherein the evaluation information table comprises laboratory marks, dyeing person marks and dyeing process data corresponding to dyed pathological sections; updating the evaluation information table, the medical image to be analyzed, a plurality of dyeing color values, the dyeing standard values and the dyeing quality of pathological sections corresponding to the medical image to be analyzed to a pathological section dyeing database.

In one embodiment, the method further comprises: acquiring the laboratory identification; acquiring the evaluation information table, the medical image to be analyzed, a plurality of dyeing color values and the dyeing standard values corresponding to unqualified dyeing quality of the pathological section from a pathological section dyeing database according to the laboratory mark; and carrying out unqualified reason analysis according to the evaluation information table, the medical image to be analyzed, the plurality of dyeing color values and the dyeing standard value to obtain unqualified reason data.

In one embodiment, after performing the failure cause analysis according to the evaluation information table, the medical image to be analyzed, the plurality of dyeing color values, and the dyeing standard value, obtaining failure cause data, the method further includes: acquiring an improvement suggestion list; and acquiring an improvement suggestion from the improvement suggestion list according to the unqualified reason data, and obtaining a laboratory improvement suggestion list.

In one embodiment, the present invention also proposes a computer device comprising at least one memory, at least one processor, the memory storing a program of computer instructions which, when executed by the processor, cause the processor to perform the method steps of:

It should be noted that the above-mentioned method for evaluating the dyeing quality of a pathological section, apparatus for evaluating the dyeing quality of a pathological section, storage medium and computer device belong to a general inventive concept, and the contents in the embodiments of a method for evaluating the dyeing quality of a pathological section, apparatus for evaluating the dyeing quality of a pathological section, storage medium and computer device are mutually applicable.

Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a non-volatile computer readable storage medium, and where the program, when executed, may include processes in the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.

Claims

1. A method for evaluating the staining quality of a pathological section, the method comprising:

obtaining a dyeing standard value, and determining the dyeing quality of a pathological section corresponding to the medical image to be analyzed according to a plurality of dyeing color values and the dyeing standard value;

Performing feature recognition on the medical image to be analyzed to obtain a plurality of dyeing color values, wherein the feature recognition comprises the following steps:

performing cell structure feature recognition according to the medical image to be analyzed to obtain a cell nucleus image and a cell plasma image,

respectively calculating color values according to the cell nucleus image and the cell plasma image to obtain a plurality of dyeing color values, wherein the plurality of dyeing color values comprise cell nucleus negative dyeing color values, cell plasma negative dyeing color values, cell nucleus positive dyeing color values and/or cell plasma positive dyeing color values;

the staining standard values include: nuclear negative staining standard value, cytoplasmic negative staining standard value, nuclear positive staining standard value, and cytoplasmic positive staining standard value.

2. The method for evaluating the quality of staining of a pathological section according to claim 1, wherein the staining standard value and the staining color value corresponding to the staining standard value are the same, or,

the dyeing standard value and the dyeing color value corresponding to the dyeing standard value adopt the tissues of the same organ and the same dyeing method, or,

the dyeing standard value and the dyeing color value corresponding to the dyeing standard value adopt tissues of the same organ, the same dyeing method and the same pathology.

3. The method for evaluating the staining quality of pathological sections according to claim 1, wherein the step of performing cell structure feature recognition according to the medical image to be analyzed to obtain a nuclear image and a cytoplasm image comprises the steps of:

dividing cell nuclei by a cell nucleus segmentation algorithm according to the medical image to be analyzed to obtain a cell nucleus image;

and dividing the cytoplasm according to the medical image to be analyzed by adopting a cytoplasm dividing algorithm to obtain a cytoplasm image.

4. The pathological section staining quality evaluation method according to claim 1, wherein the calculating of the color values from the nuclear image and the cytoplasmic image, respectively, to obtain a plurality of staining color values, the plurality of staining color values including a nuclear negative staining color value, a cytoplasmic negative staining color value, a nuclear positive staining color value, and/or a cytoplasmic positive staining color value, comprises:

classifying according to the color value of the cell nucleus image to obtain a cell nucleus negative staining image and a cell nucleus positive staining image;

classifying according to the color value of the cytoplasm image to obtain a cytoplasm negative staining image and a cytoplasm positive staining image;

And calculating color values according to the cell nucleus negative staining image, the cell nucleus positive staining image, the cell plasma negative staining image and the cell plasma positive staining image respectively to obtain a cell nucleus negative staining color value, a cell plasma negative staining color value, a cell nucleus positive staining color value and a cell plasma positive staining color value.

5. The method according to claim 1, wherein determining the quality of staining of the pathological section corresponding to the medical image to be analyzed from the plurality of staining color values and the staining standard value comprises:

scoring the dyeing color value and a dyeing standard value corresponding to the dyeing color value to obtain a dyeing color value score;

comprehensively scoring according to all the staining color value scores to obtain pathological section staining comprehensive scores;

and obtaining a comprehensive dyeing score standard value, and comparing according to the comprehensive dyeing score standard value and the comprehensive pathological section dyeing score to determine the dyeing quality of the pathological section corresponding to the medical image to be analyzed.

6. The method for evaluating the staining quality of a pathological section according to claim 5, wherein scoring the staining color value and the staining standard value corresponding to the staining color value to obtain a staining color value score comprises:

When the dyeing standard value is an RGB value, calculating the dyeing color value and a difference value before the dyeing standard value corresponding to the dyeing color value to obtain a dyeing color difference value;

scoring according to the dyeing color difference value to obtain a dyeing color value score;

and when the dyeing standard value is a range value, the dyeing color value score is full when the dyeing color value is within the range value of the dyeing standard value corresponding to the dyeing color value, and when the dyeing color value is not within the range value of the dyeing standard value corresponding to the dyeing color value, the dyeing color value score is calculated according to a preset scoring rule.

7. The method according to claim 6, wherein calculating a dyeing color value score according to a preset scoring rule when the dyeing color value is not within a range of dyeing standard values corresponding to the dyeing color value, comprises:

calculating the average value of the range value starting point and the end point of the range value of the dyeing standard value corresponding to the dyeing color value to obtain a dyeing standard value center;

when the dyeing color value is smaller than the center of the dyeing standard value, subtracting the dyeing color value from the range value starting point of the range value of the dyeing standard value corresponding to the dyeing color value to obtain a deviation difference value;

And when the dyeing color value is larger than the dyeing standard value center, subtracting the range value end point of the range value of the dyeing standard value corresponding to the dyeing color value from the dyeing color value to obtain a deviation difference value, and calculating according to the deviation difference value to obtain a dyeing color value score.

8. The method for evaluating the staining quality of a pathological section according to claim 6, wherein the staining color value comprises a channel number value of three channels, and the staining standard value comprises a channel standard value of three channels;

respectively calculating a channel difference value between the channel value of each channel and a channel standard value corresponding to the channel value;

calculating an absolute value according to the channel difference value to obtain a channel color difference value;

and carrying out weighted summation calculation according to the three channel color differences to obtain a dyeing color difference.

9. The method for evaluating the staining quality of a pathological section according to claim 6, wherein the scoring according to the staining color difference value to obtain a staining color value score comprises:

Dividing the dyeing color difference value by a preset numerical value to obtain a dyeing color value score;

or alternatively, the first and second heat exchangers may be,

scoring the dyeing color difference value as a dyeing color value;

or alternatively, the first and second heat exchangers may be,

dividing the dyeing color difference value by 255 to obtain a difference index, and subtracting the difference index from 1 to obtain a dyeing color value score.

10. The method for evaluating the staining quality of a pathological section according to any one of claims 1 to 9, wherein the digitally scanning the stained pathological section to obtain a medical image to be analyzed comprises:

digitally scanning the dyed pathological section to obtain an initial medical image;

performing binarization processing on the initial medical image to obtain a binarized medical image;

acquiring a color value with the lowest numerical value from the binarized medical image to obtain a binarized lowest color value;

determining a lowest color value of the initial medical image corresponding to the binarized lowest color value according to the binarized lowest color value;

and correcting the initial medical image according to the minimum color value of the initial medical image corresponding to the binarized minimum color value to obtain the medical image to be analyzed.

11. The pathological section staining quality evaluation method according to claim 10, wherein the performing correction processing on the initial medical image according to the lowest color value of the initial medical image corresponding to the binarized lowest color value to obtain the medical image to be analyzed comprises:

12. The method according to any one of claims 1 to 9, characterized by further comprising, after said determining the quality of staining of a pathological section corresponding to the medical image to be analyzed from a plurality of the staining color values and the staining standard values:

acquiring an evaluation information table, wherein the evaluation information table comprises laboratory marks, dyeing person marks and dyeing process data corresponding to dyed pathological sections;

updating the evaluation information table, the medical image to be analyzed, a plurality of dyeing color values, the dyeing standard values and the dyeing quality of pathological sections corresponding to the medical image to be analyzed to a pathological section dyeing database.

13. The pathological section staining quality evaluation method according to claim 12, wherein the method further comprises:

acquiring the laboratory identification;

acquiring the evaluation information table, the medical image to be analyzed, a plurality of dyeing color values and the dyeing standard values corresponding to unqualified dyeing quality of the pathological section from a pathological section dyeing database according to the laboratory mark;

And carrying out unqualified reason analysis according to the evaluation information table, the medical image to be analyzed, the plurality of dyeing color values and the dyeing standard value to obtain unqualified reason data.

14. The method according to claim 13, wherein after performing failure cause analysis based on the evaluation information table, the medical image to be analyzed, the plurality of the dyeing color values, and the dyeing standard value, obtaining failure cause data, further comprising:

acquiring an improvement suggestion list;

and acquiring an improvement suggestion from the improvement suggestion list according to the unqualified reason data, and obtaining a laboratory improvement suggestion list.

15. A pathological section staining quality evaluation apparatus, characterized in that the apparatus comprises:

the dyeing quality determining module is used for obtaining a dyeing standard value and determining the dyeing quality of the pathological section corresponding to the medical image to be analyzed according to a plurality of dyeing color values and the dyeing standard value;

The dyeing color value extraction module is specifically configured to:

performing cell structure feature recognition according to the medical image to be analyzed to obtain a cell nucleus image and a cell plasma image, and performing color value calculation according to the cell nucleus image and the cell plasma image to obtain a plurality of dyeing color values, wherein the plurality of dyeing color values comprise a cell nucleus negative dyeing color value, a cell plasma negative dyeing color value, a cell nucleus positive dyeing color value and/or a cell plasma positive dyeing color value;

16. A storage medium storing a program of computer instructions which, when executed by a processor, cause the processor to perform the steps of the method of any one of claims 1 to 14.

17. A computer device comprising at least one memory, at least one processor, the memory storing a program of computer instructions that, when executed by the processor, cause the processor to perform the steps of the method of any of claims 1 to 14.