Deep convolutional neural network-based lung cancer preventing self-service health cloud service system

A technology of convolutional neural network and neural network, applied in the field of self-service health cloud service system

Active Publication Date: 2017-02-01
汤一平
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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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 ser

Method used

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  • Deep convolutional neural network-based lung cancer preventing self-service health cloud service system
  • Deep convolutional neural network-based lung cancer preventing self-service health cloud service system
  • Deep convolutional neural network-based lung cancer preventing self-service health cloud service system

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Embodiment 1

[0120] refer to Figure 1-21 , the technical solution adopted by the present invention to solve its technical problems is:

[0121] The self-service health cloud service system for lung cancer prevention based on deep convolutional neural network includes a convolutional neural network for deep learning and training recognition, a segmentation of lung regions from CT images based on full convolutional neural network Algorithm, a deep convolutional neural network for lung cancer diagnosis and classification, and a self-service health cloud service platform for early prevention and treatment based on identified suspected lung cancer types; the block diagram of the self-service health cloud service system for lung cancer prevention is shown in figure 1 shown;

[0122] The use and preparation of the self-help health cloud service system for lung cancer prevention: users use mobile phones or other mobile devices to obtain chest X-rays or CT digital images. First, the user opens a...

Embodiment 2

[0199] The rest are the same as in Embodiment 1, except that the self-help health cloud service system for lung cancer prevention based on deep convolutional neural network of the present invention can be directly applied to hospitals and health centers at all levels, providing reference for further clinical case examination and diagnosis for doctors; This platform can also be applied in the health checkup of lung cancer screening, which reduces the workload of radiologists while improving the accuracy of lung cancer screening, and comprehensively improves the comprehensive informatization, objectification and standardization of lung cancer screening methods.

Embodiment 3

[0201] The rest are the same as in Embodiment 1, except that the self-help health cloud service system for lung cancer prevention based on deep convolutional neural network of the present invention can be used for dynamic analysis of lung lesions; The user's detailed image data, the image data of each time period can be compared and analyzed, and the corresponding changes of lung-related diseases can be observed with the development of the disease. The observation should also be dynamically analyzed with the development of the disease, especially with the There are new changes found in the original historical chest X-ray or CT image comparison; accordingly, it provides an important basis for early diagnosis and early treatment; the present invention records in detail the benefits of the lung self-clinic for users to access the health cloud service platform. The results and the time of the visit are recorded, and these information are helpful for the dynamic analysis of lung les...

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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...

Claims

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Application Information

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IPC IPC(8): G06F19/00
Inventor 汤一平郑智茵
Owner 汤一平
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