Breast nodules auxiliary diagnosis method based on DSSD and system

Abstract

The invention relates to the field of medical image technology, and particularly to a breast nodules auxiliary diagnosis method based on DSSD and a system. The system comprises a breast image workstation, a breast cloud diagnosis system and a breast diagnosis mobile terminal. The breast image workstation performs breast image acquisition. The breast cloud diagnosis system comprise training set anda testing set preprocessing, marking and neural network discriminating, wherein the training set and the testing set preprocessing comprises multi-scale image de-noising and enhancing. The method comprises the steps of acquiring a breast graph by the breast image workstation, performing discriminating through mainly using a DSSD neural network, and finally transmitting a result which is obtainedthrough processing of the breast cloud diagnosis system to the breast diagnosis mobile terminal. According to the method and the system, a computer-aided diagnosis (CAD) system based on deep learningis developed for aiming at the field of the medical image (unnatural image), thereby supplying a second opinion for diagnosis to a radiology department doctor, and more effectively assisting the doctor in performing diagnosis.

Description

technical field [0001] The invention relates to the technical field of medical imaging, in particular to a DSSD-based auxiliary diagnosis method and system for breast nodules. Background technique [0002] Breast cancer is a malignant tumor that occurs in the glandular epithelial tissue of the mammary gland, and has always been one of the terrorist killers that threaten women's health. The global incidence of breast cancer has been on the rise since the late 1970s. There is a very high probability of breast cancer in China, and it is increasing at a rate of 14% per year, and it is showing a younger trend. Clinically, mammary gland molybdenum palladium is an effective examination method, but it has the disadvantage of high false positive rate; in addition, clinical doctors are highly subjective, resulting in a high rate of misdiagnosis. [0003] Since the 1980s, researchers have successively proposed some computer methods for auxiliary diagnosis of mammography images, and m...

AI Technical Summary

Problems solved by technology

Clinically, mammary gland molybdenum palladium is an effective examination method, but it has the disadvantage of high false positive rate; in addition, clinical doctors are relatively subjective, resulting in a high rate of misdiagnosis

Images