Deep learning referral suggestion and tumour discrimination using explainable artificial intelligence applied to multiparametric MRI.

Journal: European radiology
Published Date: May 8, 2023

Abstract

OBJECTIVES: An appropriate and fast clinical referral suggestion is important for intra-axial mass-like lesions (IMLLs) in the emergency setting. We aimed to apply an interpretable deep learning (DL) system to multiparametric MRI to obtain clinical referral suggestion for IMLLs, and to validate it in the setting of nontraumatic emergency neuroradiology.

Authors

  • Hyungseob Shin
    School of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea.
  • Ji Eun Park
    Department of Anatomy and Cell Biology, College of Medicine, Dong-A University, Busan 602-714, Korea.
  • Yohan Jun
    School of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea.
  • Taejoon Eo
    School of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.
  • Jeongryong Lee
    Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea.
  • Ji Eun Kim
    Department of Biomaterials Science, College of Natural Resources & Life Science/Life and Industry Convergence Research Institute, Pusan National University, Miryang 627-706, Republic of Korea.
  • Da Hyun Lee
    Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul, 05505, Korea.
  • Hye Hyeon Moon
    Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
  • Sang Ik Park
    Department of Radiology, Chung-Ang University Hospital, Seoul, Korea.
  • Seonok Kim
    Department of Clinical Epidemiology and Biostatistics, Asan Medical Centre, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Dosik Hwang
    School of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea. dosik.hwang@yonsei.ac.kr.
  • Ho Sung Kim
    Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.

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