CN-116503321-B - Pathological index determination method, device, equipment and medium

CN116503321BCN 116503321 BCN116503321 BCN 116503321BCN-116503321-B

Abstract

The application discloses a pathological index determining method, a device, equipment and a storage medium, wherein the method comprises the steps of obtaining a pathological image of bone marrow to be processed; the method comprises the steps of preprocessing a bone marrow pathology image to be processed to obtain a bone marrow sample image set, carrying out image processing on the bone marrow sample image set to obtain a bone marrow tissue region image, carrying out image processing on the bone marrow tissue region image to determine a bone marrow adipose tissue region and a bone trabecular tissue region, removing the bone marrow adipose tissue region and the bone trabecular tissue region to obtain a processed bone marrow tissue image, inputting the processed bone marrow tissue image into a trained image segmentation model to obtain a bone marrow fiber region, and carrying out statistical analysis on fibrosis degree according to the bone marrow tissue region image and the bone marrow fiber region to determine pathology indexes. According to the scheme, the layout details of the pathological image can be extracted, so that the fibrosis degree is comprehensively and finely counted and analyzed, and the accuracy of determining the pathological indexes is improved.

Inventors

ZHOU FENGYUAN
YAN XU
QI QIANQIAN
ZHANG LEI
SUN QI
YU DANDAN
WANG HUANPENG
ZHENG GANG
Qiao chang
Zhao Mengchong
SHI XIANGJIE

Assignees

周冯源
中国医学科学院血液病医院(中国医学科学院血液学研究所)

Dates

Publication Date: 20260505
Application Date: 20230310

Claims (11)

1. A method of determining a pathology index, the method comprising: acquiring a bone marrow pathological image to be treated; preprocessing the bone marrow pathological image to be processed to obtain a bone marrow sample image set; performing image processing on the bone marrow sample image set to obtain a bone marrow tissue area image; Performing image processing on the bone marrow tissue area image, determining a bone marrow adipose tissue area and a bone trabecular tissue area, and removing the bone marrow adipose tissue area and the bone trabecular tissue area to obtain a processed bone marrow tissue image; inputting the processed bone marrow tissue image into a trained image segmentation model to obtain a binary image, and calculating the outline of the binary image to obtain a bone marrow fiber region; Obtaining a bone marrow tissue area image of a known initial fibrosis level, calculating bone marrow fiber index information of the bone marrow tissue area image based on the bone marrow fiber area, correcting the initial fibrosis level according to the bone marrow fiber index information to obtain an intermediate fibrosis level, wherein the bone marrow fiber index information comprises bone marrow tissue area, bone marrow fiber area and bone marrow fiber area ratio, traversing the bone marrow tissue area image, performing block treatment on the bone marrow tissue area image to obtain a plurality of block bone marrow tissue area images, calculating fiber density information of each block bone marrow tissue area image, constructing a relationship between the intermediate fibrosis level and fiber density based on the fiber density information, obtaining the fibrosis degree of the block bone marrow tissue area image of each fibrosis level according to the relationship between the intermediate fibrosis level and fiber density, and statistically analyzing the fibrosis degree of all the block bone marrow tissue area images to determine a pathological index.
2. The method of claim 1, wherein preprocessing the bone marrow pathology image to be processed to obtain a set of bone marrow sample images, comprises: Converting the bone marrow pathological image to be processed into a bone marrow image in RGBA format; Acquiring pixel values of an A channel in the bone marrow image in the RGBA format, and dividing the bone marrow pathological image to be processed according to the pixel values of the A channel and a preset A channel threshold value to obtain a plurality of bone marrow samples; And filtering each bone marrow sample in the plurality of bone marrow samples according to a preset size pixel threshold value to obtain a bone marrow sample image set.
3. The method according to claim 1 or 2, wherein image processing the set of bone marrow sample images to obtain a bone marrow tissue area image comprises: For each bone marrow sample image in the bone marrow sample image collection, converting the bone marrow sample image into a bone marrow tissue image in BGR format; Performing channel separation processing on the bone marrow tissue image to obtain a B channel image, an R channel image and a G channel image, and converting the B channel image, the R channel image and the G channel image to obtain a binarized image; and performing edge optimization and contour extraction processing on the bone marrow tissue image based on the B channel image, the R channel image and the binarization image to obtain a bone marrow tissue region image.
4. The method of claim 1, wherein image processing the image of the bone marrow tissue area to determine a bone marrow adipose tissue area comprises: Converting the bone marrow tissue area image into a LAB-format bone marrow tissue area image; Performing block processing on the LAB format bone marrow tissue area image according to a fixed size to obtain a plurality of block images; for each block image in the plurality of block images, determining a pixel value of each block image in an L color channel, and determining a multi-pixel region according to the pixel value of the L color channel and a preset pixel threshold interval; Determining a single fat droplet region and a multi-fat aggregation region based on morphological features of the fat-free region; from the single fat drop region and the multiple fat aggregation region, a bone marrow adipose tissue region is determined.
5. The method of claim 1, wherein image processing the bone marrow tissue area image to determine a bone trabecular tissue area comprises: performing image enhancement processing on the bone marrow tissue area image to obtain an enhanced image; Converting the enhanced image into a bone marrow mask binary image; calculating pixel values of all outlines of the bone marrow mask binary image; Filtering the bone marrow mask binary image according to a first size threshold, a second size threshold and the pixel value to obtain a complete bone trabecular region and a bone trabecular fragment region, wherein the first size threshold is larger than the second size threshold; A trabecular tissue region is determined based on the intact trabecular region and the trabecular fragment region.
6. The method of claim 1, wherein inputting the processed bone marrow tissue image into a trained image segmentation model to obtain a binary image comprises: Performing blocking treatment on the treated bone marrow tissue image to obtain a plurality of blocked bone marrow tissue images; Inputting each segmented bone marrow tissue image into an encoder of the image segmentation model to obtain a feature map; the feature map passes through a decoder of the image segmentation model to obtain a block binary map; and performing splicing treatment on the plurality of block binary images to obtain a binary image.
7. The method of claim 1, wherein calculating myelofiber index information of the image of the myelotissue region based on the myelofiber region comprises: calculating a bone marrow tissue area based on the segmented bone marrow tissue area image; calculating the number of the bone marrow fibers and the area of the bone marrow fiber area according to the bone marrow fiber area; and obtaining the area ratio of the bone marrow fiber area based on the area of the bone marrow fiber area and the area of the bone marrow tissue.
8. The method of claim 6, wherein the image segmentation model is constructed by: preprocessing the acquired sample pathology image to obtain a sample bone marrow tissue area image; Performing block processing on the sample marrow tissue area image to obtain a plurality of sample block marrow tissue images, wherein each sample block marrow tissue image comprises a marked marrow fiber area; inputting each sample block bone marrow tissue image into an image segmentation model to be constructed for processing to obtain a plurality of sample block binary images; splicing the plurality of sample block binary images to obtain a sample binary image; calculating the outline of the sample binary image to obtain a predicted bone marrow fiber area; And based on the loss function between the predicted myelofiber region and the marked myelofiber region, performing iterative training on the image segmentation model to be constructed by adopting an iterative algorithm according to the minimization of the loss function to obtain an image segmentation model.
9. A pathology index determination apparatus, the apparatus comprising: the acquisition module is used for acquiring a bone marrow pathological image to be processed; The pretreatment module is used for carrying out pretreatment on the bone marrow pathological image to be treated to obtain a bone marrow sample image set; The first processing module is used for performing image processing on the bone marrow sample image set to obtain a bone marrow tissue area image; The second processing module is used for performing image processing on the bone marrow tissue area image, determining a bone marrow adipose tissue area and a bone trabecular tissue area, and removing the bone marrow adipose tissue area and the bone trabecular tissue area to obtain a processed bone marrow tissue image; the fiber region determining module is used for inputting the processed bone marrow tissue image into a trained image segmentation model to obtain a binary image, and calculating the outline of the binary image to obtain a bone marrow fiber region; The statistical analysis module is used for acquiring a bone marrow tissue area image of a known initial fibrosis level, calculating bone marrow fiber index information of the bone marrow tissue area image based on the bone marrow fiber area, correcting the initial fibrosis level according to the bone marrow fiber index information to obtain an intermediate fibrosis level, traversing the bone marrow tissue area image, carrying out block treatment on the bone marrow tissue area image to obtain a plurality of block bone marrow tissue area images, calculating fiber density information of each block bone marrow tissue area image, constructing a relationship between the intermediate fibrosis level and the fiber density based on the fiber density information, obtaining the fibrosis degree of the block bone marrow tissue area image of each fibrosis level according to the relationship between the intermediate fibrosis level and the fiber density, and carrying out statistical analysis on the fibrosis degree of all the block bone marrow tissue area images to determine a pathological index.
10. Computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the pathology index determination method according to any one of claims 1-8 when executing the computer program.
11. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements a pathology index determination method according to any one of claims 1-8.

Description

Pathological index determination method, device, equipment and medium Technical Field The invention relates to the technical field of medical treatment, in particular to a method, a device, equipment and a medium for determining a pathological index. Background With the continuous development of medical technology, the analysis and screening based on pathological images are important means for disease diagnosis and treatment in modern medicine, such as the analysis of bone marrow slice images, and specific analysis is generally performed on the distribution/morphology aspect of bone marrow tissue slice images, and pathological indexes of bone marrow fibrosis are determined by observing pathological tissues, so that auxiliary means are provided for stages of drug test, postoperative analysis, medical planning, treatment effect evaluation and the like. Currently, in the related art, the myelofibrosis pathological index is determined by manually observing based on myelopathology images, but the mode only depends on manual knowledge storage and reading experience, and lacks objectivity, so that the accuracy of determining the myelofibrosis pathological index is lower. Disclosure of Invention In view of the foregoing drawbacks or shortcomings of the prior art, it is desirable to provide a pathology index determination method, apparatus, device, and medium. In a first aspect, the present invention provides a method for determining a pathological index, the method comprising: acquiring a bone marrow pathological image to be treated; preprocessing the bone marrow pathological image to be processed to obtain a bone marrow sample image set; performing image processing on the bone marrow sample image set to obtain a bone marrow tissue area image; Performing image processing on the bone marrow tissue area image, determining a bone marrow adipose tissue area and a bone trabecular tissue area, and removing the bone marrow adipose tissue area and the bone trabecular tissue area to obtain a processed bone marrow tissue image; inputting the processed bone marrow tissue image into a trained image segmentation model to obtain a binary image, and calculating the outline of the binary image to obtain a bone marrow fiber region; And according to the image of the bone marrow tissue area and the bone marrow fiber area, the fibrosis degree is statistically analyzed, and the pathological index is determined. In a second aspect, an embodiment of the present application provides a pathology index determination apparatus, including: the acquisition module is used for acquiring a bone marrow pathological image to be processed; The pretreatment module is used for carrying out pretreatment on the bone marrow pathological image to be treated to obtain a bone marrow sample image set; The first processing module is used for performing image processing on the bone marrow sample image set to obtain a bone marrow tissue area image; The second processing module is used for performing image processing on the bone marrow tissue area image, determining a bone marrow adipose tissue area and a bone trabecular tissue area, and removing the bone marrow adipose tissue area and the bone trabecular tissue area to obtain a processed bone marrow tissue image; the fiber region determining module is used for inputting the processed bone marrow tissue image into a trained image segmentation model to obtain a binary image, and calculating the outline of the binary image to obtain a bone marrow fiber region; and the statistical analysis module is used for statistically analyzing the fibrosis degree according to the image of the bone marrow tissue area and the bone marrow fiber area and determining a pathological index. In a third aspect, an embodiment of the present application provides an apparatus, including a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the pathology index determination method according to the first aspect as described above when executing the program. In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having stored thereon a computer program for implementing the pathology index determination method of the above first aspect. According to the pathological index determination method, device, equipment and medium provided by the embodiment of the application, a bone marrow pathological image to be processed is obtained, the bone marrow pathological image to be processed is preprocessed to obtain a bone marrow sample image set, then the bone marrow sample image set is subjected to image processing to obtain a bone marrow tissue area image, the bone marrow tissue area image is subjected to image processing to determine a bone marrow adipose tissue area and a bone trabecular tissue area, the bone marrow adipose tissue area and the bone trabecular tissue area are removed to obtain a processed bone marrow tissue image