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

Abstract

The invention discloses a deep convolutional neural network-based lung cancer preventing self-service health cloud service system. The system comprises a convolutional neural network used for deep learning and training identification, a segmentation module which segments out a lung region from a CT image based on a full convolutional neural network, a deep convolutional neural network used for lung cancer diagnosis classification, and a self-service health cloud service platform used for performing early prevention and treatment according to an identified suspected lung cancer type. According to the system, the automation and intelligentization level of mobile internet-based lung cancer screening can be effectively improved, more citizens can know and participate in self-service health detection, assessment and guidance, the sensitivity, specificity and accuracy of early lung cancer screening and clinical diagnosis are improved, the lung cancer can be early discovered, early diagnosed and early treated, and the self-health management capability is enhanced.

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 A self-service health cloud service system for early detection and early diagnosis of lung cancer. Background technique [0002] Lung cancer is the most common malignant tumor in the world today, and its mortality rate ranks first among all kinds of tumors, posing a great threat to human health and life. In my country, lung cancer causes about 500,000 patients to die every year, accounting for 28% of the total cancer cases, while the 5-year survival rate of lung cancer patients is only 14%. However, studies have shown that the 10-year survival rate after surgery for stage I lung cancer can reach 92%. Therefore, the key t...

AI Technical Summary

Problems solved by technology

[0034] In summary, there are still several thorny problems in the early diagnosis of lung cancer using convolutional neural networks based on deep learning: 1) how to accurately segment the overall image of the lungs from the complex background; 2) how to Use as little labeled lung cancer image data as possible to accurately obtain various feature data of lung cancer; 3) How to build a highly automated self-service health cloud service system for lung cancer prevention; 4) How to automatically obtain lung cancer features through deep learning and network training 5) How to enable users to conveniently use the mobile Internet and smart phones to achieve self-health care, and realize early detection, early diagnosis and early treatment of lung cancer; 6) How to provide users with more accurate, more convenient, cheaper, and more Effective health cloud service

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