Diagnostic performance for detecting bone marrow edema of the hip on dual-energy CT: Deep learning model vs. musculoskeletal physicians and radiologists.

Journal: European journal of radiology
Published Date:

Abstract

PURPOSE: To compare the diagnostic performance of a deep learning (DL) model with that of musculoskeletal physicians and radiologists for detecting bone marrow edema on dual-energy CT (DECT).

Authors

  • ChunSu Park
    School of Biomedical Convergence Engineering, College of Information and BioMedical Engineering, Pusan National University, Yangsan, Korea.
  • Minwoo Kim
    School of Electronics and Information Engineering, Korea Aerospace University, Goyang-si 10540, Korea. minwoo@kau.kr.
  • Chankue Park
    Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Korea.
  • Wookon Son
    Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Korea.
  • Sang-Min Lee
    Department of Orthopedics, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Korea.
  • Hee Seok Jeong
    Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Korea.
  • JeongWoon Kang
    School of Biomedical Convergence Engineering, College of Information and BioMedical Engineering, Pusan National University, Yangsan, Korea.
  • Min-Hyeok Choi
    Department of Preventive and Occupational & Environmental Medicine, Pusan National University Yangsan Hospital, Pusan National University, Yangsan, Korea.