A self-help health cloud service system for breast cancer prevention based on deep convolutional neural network

Abstract

The invention discloses a self-service health cloud service system for breast cancer prevention based on a deep convolutional neural network, which mainly includes a convolutional neural network for deep learning and training recognition, and a mammography image based on a full convolutional neural network A segmentation module for the middle breast region, a deep convolutional neural network for BI‑RADS classification and assessment, and a cloud service platform for breast self-help health based on identified breast intramammary structures, masses, and calcification types. The invention can effectively improve the automation and intelligence level of breast cancer screening based on the mobile Internet, enable more women to understand and participate in self-service health detection, evaluation, and guidance, thereby improving people's health awareness and self-health management capabilities.

Description

technical field [0001] The present invention relates to the application of technologies such as medical image diagnosis, mobile Internet, database management, computer vision, image processing, pattern recognition, deep neural network and deep learning in the field of self-service health care, especially relates to a deep convolutional neural network-based Self-service health cloud service system for early detection and early diagnosis of breast cancer. Background technique [0002] In recent years, the incidence of breast cancer in our country has been increasing year by year, especially in some big cities, such as Shanghai, Beijing and other places, breast cancer has jumped to the first place in the incidence of malignant tumors in women. [0003] Screening is an important method for early detection of breast cancer. High-quality mammography (ie, mammography) combined with clinical outpatient and breast ultrasonography is currently the most important screening method. Mam...

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Problems solved by technology

[0030] To sum up, there are still several thorny problems in the early diagnosis of breast cancer using convolutional neural networks based on deep learning: 1) how to accurately segment the overall image of the breast from the complex background; 2) how to Use as little labeled breast cancer image data as possible to accurately obtain various characteristic data of breast cancer; 3) How to build a highly automated self-service health cloud service system for breast cancer prevention; 4) How to automatically Obtain breast cancer characteristic data; 5) How to enable users to conveniently use mobile Internet and smart phones to achieve self-health care, and realize early detection, early diagnosis and early treatment of breast cancer; 6) How to provide users with more accurate, more convenient, more For cheap, more effective health cloud services

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