Associating Knee Osteoarthritis Progression with Temporal-Regional Graph Convolutional Network Analysis on MR Images.

Journal: Journal of magnetic resonance imaging : JMRI
PMID:

Abstract

BACKGROUND: Artificial intelligence shows promise in assessing knee osteoarthritis (OA) progression on MR images, but faces challenges in accuracy and interpretability.

Authors

  • Jiaping Hu
    Department of Medical Imaging, The Third Affiliated Hospital of Southern Medical University (Academy of OrthopedicsĀ· Guangdong Province), Guangzhou, China.
  • Junyi Peng
    School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China.
  • Zidong Zhou
    School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China.
  • Tianyun Zhao
    Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA.
  • Lijie Zhong
    Postgraduates at the First Clinical Medicine of Gannan Medical University, Ganzhou, Jiangxi, China.
  • Keyan Yu
    Department of Medical Imaging, The Third Affiliated Hospital of Southern Medical University (Academy of Orthopedics Guangdong Province), Guangzhou, PR China.
  • Kexin Jiang
    College of Medicine, Southwest Jiaotong University, Chengdu, China.
  • Tzak Sing Lau
    Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia, USA.
  • Chuan Huang
    Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York chuan.huang@stonybrookmedicine.edu.
  • Lijun Lu
    School of Biomedical Engineering, Southern Medical University, Guangzhou, 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.