Computer-aided diagnosis of cystic lung diseases using CT scans and deep learning.

Journal: Medical physics
PMID: 39422997

Abstract

BACKGROUND: Auxiliary diagnosis of different types of cystic lung diseases (CLDs) is important in the clinic and is instrumental in facilitating early and specific treatments. Current clinical methods heavily depend on accumulated experience, restricting their applicability in regions with less developed medical resources. Thus, how to realize the computer-aided diagnosis of CLDs is of great clinical value.

Authors

  • ZhiBin Zhu
    School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, Guangxi Province, China.
  • Wenyu Xing
    Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai 200438, China; Human Phenome Institute, Fudan University, Shanghai 200438, China.
  • Yanping Yang
    Shanghai Institute of Infectious Disease and Biosecurity, Fudan University Shanghai 200032 China.
  • Xin Liu
    Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences, Weifang, Shandong, China.
  • Tao Jiang
    Department of Respiratory and Critical Care Medicine, Center for Respiratory Medicine, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, China.
  • Xingwei Zhang
    Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.
  • Yuanlin Song
    Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China; Shanghai Key Laboratory of Lung Inflammation and Injury, Shanghai, 200032, China.
  • Dongni Hou
    Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China; Shanghai Key Laboratory of Lung Inflammation and Injury, Shanghai, 200032, China. Electronic address: hou.dongni@zs-hospital.sh.cn.
  • Dean Ta

Keywords

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