Abstract

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Author(s):: XIE Haojie1; LU Mingli2; ZHANG Chen1; ZHOU Lixiang3; TENG Yidi4; WANG Mingming1; 1. School of Electrical Engineering, Yancheng Institute of Technology, Yancheng 221051, China 2. School of Electrical and Automation Engineering, Changshu Institute of Technology, Changshu 215500, China 3. School of Mechanical and Electrical Engineering, Soochow University, Suzhou 215031, China 4. School of Electronic and Information Engineering, Changshu Institute of Technology, Changshu 215500, China

Keywords:: Keywords: pulmonary tuberculosis medical image automatic detection deep learning review

Abstract:: The automatic detection of tuberculosis lesions based on medical imaging has become a research hotspot in medical image processing. A comprehensive review of relevant researches and applications pertaining to deep learning in tuberculosis lesion detection is provided, which elucidates the experimental benchmarks in tuberculosis analysis, covering public datasets of pulmonary medical images and recent research advancements in tuberculosis detection and classification competitions, introduces emerging trends in deep learning methods and applications in tuberculosis detection, and analyzes the challenges existing in tuberculosis diagnosis using deep learning. The review summarizes and provides insights into the research advances and challenges of these technologies from the aspects of technical characteristics, performance advantages, and application prospects.