Deep Learning-Based Automatic Detection and Grading of Motion-Related Artifacts on Gadoxetic Acid-Enhanced Liver MRI.

Journal: Investigative radiology
Published Date:

Abstract

OBJECTIVES: The aim of this study was to develop and validate a deep learning-based algorithm (DLA) for automatic detection and grading of motion-related artifacts on arterial phase liver magnetic resonance imaging (MRI).

Authors

  • TaeYong Park
    School of Computer Science and Engineering, Soongsil University, Seoul, Korea.
  • Dong Wook Kim
    3 Department of Orthopedic Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
  • Sang Hyun Choi
    From the Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine.
  • Seungwoo Khang
    School of Computer Science and Engineering, Soongsil University, Seoul.
  • Jimi Huh
    Department of Radiology, Ajou University School of Medicine and Graduate School of Medicine, Ajou University Hospital, Suwon, Korea.
  • Seung Baek Hong
    Department of Radiology, Pusan National University Hospital, Busan, Korea.
  • Tae Young Lee
    Department of Radiology, Ulsan University Hospital, Ulsan, Korea.
  • Yousun Ko
    Biomedical Research Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Republic of Korea.
  • Kyung Won Kim
    Department of Pediatrics, Severance Children's Hospital, Institute of Allergy, Institute for Immunology and Immunological Diseases, Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea. kwkim@yuhs.ac.
  • Seung Soo Lee
    From the Department of Computer Science, Hanyang University, Seoul, Republic of Korea (K.J.C.); Department of Radiology and Research Institute of Radiology (J.K.J., S.S.L., Y.S.S., W.H.S., H.S.K., J.Y., J.H.K., S.Y.K.) and Department of Diagnostic Pathology (E.S.Y.), Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, South Korea; Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea (J.Y.C.); Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea (Y.L.); and Department of Radiology, Hanyang University Medical Center, Hanyang University School of Medicine, Seoul, Korea (B.K.K.).