Automatic measurement of the patellofemoral joint parameters in the Laurin view: a deep learning-based approach.

Journal: European radiology
Published Date:

Abstract

OBJECTIVES: To explore the performance of a deep learning-based algorithm for automatic patellofemoral joint (PFJ) parameter measurements from the Laurin view.

Authors

  • Tuya E
    Department of Radiology, 26447Peking University First Hospital, Beijing, PR China.
  • Rile Nai
    Department of Radiology, 26447Peking University First Hospital, Beijing, PR China.
  • Xiang Liu
    College of Agricultural Science and Engineering, Hohai University, Nanjing 210098, China; Anhui Provincial Key Laboratory of Environmental Pollution Control and Resource Reuse, Anhui Jianzhu University, Hefei 230009, China.
  • Cen Wang
    Department of Radiology, Beijing Nuclear Industry Hospital, Beijing, PR China.
  • Jing Liu
    Department of Ophthalmology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Shijia Li
    Beijing Smart Tree Medical Technology Co. Ltd., No.24 Huangsi Street, Xicheng District, Beijing, 100011, China.
  • Jiahao Huang
    Beijing Smart Tree Medical Technology Co. Ltd., No.24, Huangsi Street, Xicheng District, Beijing, 100011, China.
  • Junhua Yu
    Beijing Smart Tree Medical Technology Co. Ltd., No.24 Huangsi Street, Xicheng District, Beijing, 100011, China.
  • Yaofeng Zhang
    Beijing Smart Tree Medical Technology co. Ltd., Beijing, China.
  • Weipeng Liu
    College of Materials and Energy, South China Agricultural University, Guangzhou, 510642, China.
  • Xiaodong Zhang
    The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • XiaoYing Wang