Lower-extremity fatigue fracture detection and grading based on deep learning models of radiographs.

Emergency Medicine Orthopedics
Journal: European radiology
Published Date:

Abstract

OBJECTIVES: To identify the feasibility of deep learning-based diagnostic models for detecting and assessing lower-extremity fatigue fracture severity on plain radiographs.

Authors

  • Yanping Wang
    The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
  • Yuexiang Li
    Computer Vision Institute, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China.
  • Guang Lin
    Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China.
  • Qirui Zhang
    Department of Medical Imaging, Jinling Hospital, Southern Medical University, No.305, Zhongshan East Road, Nanjing, 210002, China.
  • Jing Zhong
    Department of Cardiothoracic Surgery, The Affiliated Dongnan hospital of Xiamen University, Zhangzhou 363000, China.
  • Yan Zhang
    Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, 110032, China.
  • Kai Ma
    Tencent Jarvis Lab, Shenzhen, 518057, China.
  • Yefeng Zheng
  • Guangming Lu
    Department of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China.
  • Zhiqiang Zhang
    Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.