Automatic classification method and system for breast cancer pathological sections

Abstract

The invention discloses an automatic classification method and system for breast cancer pathological sections, and the method comprises the steps: constructing a deep semantic segmentation network forthe semantic segmentation of pathological tissue sections, and obtaining a lesion region; constructing a morphological feature set according to the obtained lesion area; constructing a pathological tissue slice classification model based on the morphological feature set; and classifying the n pathological tissue sections of the patient by using the classification model, and calculating the pN stage of the patient according to the classification result of the n sections. According to the automatic classification method for the breast cancer pathological sections, the pN stages of lymphatic metastasis of patients can be automatically predicted, compared with an existing method that only lesion areas in the sections are segmented, the requirements of doctors for an intelligent diagnosis system are better met, and research and landing of an existing intelligent diagnosis method and system are promoted.

Description

technical field [0001] The invention belongs to the field of medical pathological image processing, and more specifically relates to an automatic classification method and system for breast cancer focus metastasis stage. Background technique [0002] Breast cancer is a malignant tumor that occurs in the glandular epithelial tissue of the breast. 99% of breast cancers occur in women and only 1% in men. It can be said that breast cancer has become a common tumor that threatens women's physical and mental health. The mammary gland is not an important organ to maintain the life activities of the human body. Breast cancer in situ is not fatal; but once the cancer cells fall off, the free cancer cells can spread throughout the body with the blood or lymph fluid, forming metastasis, which is life-threatening. Therefore, the correct prediction of the stage of cancer metastasis can detect high-risk patients with poor prognosis as early as possible, which is of great significance to...

AI Technical Summary

Problems solved by technology

[0005] In view of the defects of the prior art, the purpose of the present invention is to provide an automatic classification method and system for the metastasis stage of breast cancer lesions, aiming to solve the problems of cumbersome manual judgment process and low accuracy in the existing stage of breast cancer metastasis

Images