Deep learning based pulmonary nodule detection method research

 In the development of modern social and economic construction, the level of scientific research and technology in various countries is getting higher and higher. The medical field began to use intelligent algorithms for detection and analysis, and achieved excellent results in practice. It is known that lung cancer is one of the most common diseases affecting human life and health, among which it ranks the first among male malignant tumor diseases and the second among female malignant tumor diseases. On the basis of understanding the research status of intelligent algorithms in the new era, this paper mainly studies the principle of tuberculosis detection methods with deep learning as the core according to the tuberculosis detection methods proposed by researchers in recent years. In the end, deep learning could help medical researchers detect more TB, improving the accuracy and sensitivity of actual tests.