Mammary gland nodule auxiliary diagnosis method and system based on YOLOV3

Abstract

The invention discloses a mammary gland nodule auxiliary diagnosis method and a mammary gland nodule auxiliary diagnosis system. The system comprises a mammary gland image acquisition device, a mammary gland diagnosis system and a mammary gland diagnosis terminal. The mammary gland image acquisition equipment is used for shooting four types of Kinect images by using Kinect equipment. The mammary gland diagnosis system is used for image preprocessing, labeling and discrimination by using a YOLOv3 neural network. Finally, a result obtained by processing of the mammary gland diagnosis system is sent to a mammary gland diagnosis terminal. The recognition results of the four types of Kinect images are fused to serve as auxiliary diagnosis results to be sent to a doctor for final diagnosis. Thejudgment of mammary gland nodules is achieved. According to the mammary gland nodule auxiliary diagnosis system, the mammary gland nodule auxiliary diagnosis system is completed on the basis of the intelligent image processing technology and the neural network. The workload of doctors can be reduced to a certain extent, and the working efficiency of the doctors is improved.

Description

technical field [0001] The invention relates to the technical field of medical imaging, in particular to a YOLOV3-based auxiliary diagnosis method and system for breast nodules. Background technique [0002] Breast cancer is the most common type of tumor among women. Early diagnosis and screening of breast cancer is beneficial to improve the 5-year survival rate of patients, which is of great clinical significance Clinically, mammary gland molybdenum palladium is an effective inspection method, but it has the disadvantage of high false positive rate; in addition, clinical doctors Strong subjectivity, resulting in a high rate of misdiagnosis. [0003] At present, imaging diagnosis mainly relies on manual reading, however, the increasing amount of image data also brings great challenges to manual reading. In order to provide doctors with effective auxiliary diagnosis information, computer-aided diagnosis based on intelligent image processing technology. Computer-aided diagn...

AI Technical Summary

Problems solved by technology

Early diagnosis and screening of breast cancer is beneficial to improve the 5-year survival rate of patients, which is of great clinical significance Clinically, mammary gland molybdenum palladium is an effective inspection method, but it has the disadvantage of high false positive rate; in addition, clinical doctors Strong subjectivity, resulting in a high rate of misdiagnosis

[0003] The current imaging diagnosis mainly relies on manual film reading. However, the increasing amount of image data also brings great challenges to manual film reading.

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