Faster R-CNN pulmonary tuberculosis symptom detection system and method based on FPN

A detection system and tuberculosis technology, applied in the field of computer vision, can solve the problems of lack of radiological diagnosticians, high death toll, misdiagnosis or missed diagnosis, etc., and achieve the effects of reducing labor intensity, improving accuracy, and reducing the risk of delayed treatment
CN110175993AInactive Publication Date: 2019-08-27THE FIRST AFFILIATED HOSPITAL OF MEDICAL COLLEGE OF XIAN JIAOTONG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
THE FIRST AFFILIATED HOSPITAL OF MEDICAL COLLEGE OF XIAN JIAOTONG UNIV
Publication Date
2019-08-27
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention discloses an automatic pulmonary tuberculosis detection system on an X-ray chest radiograph based on a characteristic pyramid network (FPN). An X-ray chest radiograph of pulmonary tuberculosis is marked; a Faster R-CNN network learning module with an FPN as the rear end is adopted for training and learning, pulmonary tuberculosis lesion symptoms are mastered, and the automatic diagnosis and detection capacity of the pulmonary tuberculosis lesion symptoms is obtained, so that the automatic detection, positioning and probability prediction of the pulmonary tuberculosis lesion are achieved, and a final pulmonary tuberculosis detection result is obtained. The FPN serves as the rear end of the detection network, the semantic features in a multi-scale network layer can be better combined, each layer is independently predicted, and fusion is finally carried out, so that focuses of different scales can be better detected. Based on a recognition technology of the deep learning network to the digital image, the automatic detection, positioning and probability prediction of the tuberculosis focus are realized, the accuracy of the focus detection is improved, and the risk of thedelayed treatment of a tuberculosis patient is reduced.
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Description

technical field

[0001] The invention relates to a target detection task in the field of computer vision, in particular to a Faster R-CNN pulmonary tuberculosis sign detection system and method based on a Feature Pyramid Network (FPN). Background technique

[0002] Tuberculosis is an infectious disease caused by the bacterium Mycobacterium tuberculosis, which spreads mainly from person to person through the air and affects the lungs. Tuberculosis is the tenth leading cause of death worldwide, even higher than AIDS. According to WHO estimates, in 2017, there were about 1.7 billion latent tuberculosis infected people in the world, with a latent infection rate of 23%. There were about 10 million new tuberculosis patients worldwide, and 1.57 million people died of tuberculosis, including 300,000 people who died of HIV infection. More than 95% of tuberculosis deaths occur in developing countries, and my country is one of the countries with high burden of tuberculosis. However, if...

Claims

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