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The authors of this study aimed to develop an artificial intelligence (AI)-based fully automated CT image analysis system in order to detect and diagnose pulmonary tuberculosis (TB). This was achieved through the retrospective use of 892 chest CT scans from pathogen-confirmed TB patients. It was found that the end-to-end AI system based on chest CT is able to achieve human-level diagnostic performance in the early detection and clinical management of patients with pulmonary TB.

Key points

  • Deep learning allows automatic detection, diagnosis, and evaluation of pulmonary tuberculosis.
  • Artificial intelligence helps clinicians to assess patients with tuberculosis.
  • Pulmonary tuberculosis disease activity and treatment management can be improved.

Article: A fully automatic artificial intelligence-based CT image analysis system for accurate detection, diagnosis, and quantitative severity evaluation of pulmonary tuberculosis

Authors: Chenggong Yan, Lingfeng Wang, Jie Lin, Jun Xu, Tianjing Zhang, Jin Qi, Xiangying Li, Wei Ni, Guangyao Wu, Jianbin Huang, Yikai Xu, Henry C. Woodruff & Philippe Lambin

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