Deep learning-based k-space-to-image reconstruction and super resolution for diffusion-weighted imaging in whole-spine MRI.

Journal: Magnetic resonance imaging
PMID:

Abstract

PURPOSE: To assess the feasibility of deep learning (DL)-based k-space-to-image reconstruction and super resolution for whole-spine diffusion-weighted imaging (DWI).

Authors

  • Dong Kyun Kim
    Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • So-Yeon Lee
    From the Department of Radiology, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Republic of Korea (J.H.H.); Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea (J.Y.J., A.J., S.Y.L., H.P., S.E.L., S.K.); Division of Biomedical Engineering, Hankuk University of Foreign Studies, Gyeonggi-do, Republic of Korea (Y.N.); and Department of Biomedical Engineering, Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, Republic of Korea (S.P.).
  • Jinyoung Lee
    Digital Signal Processing & Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei University, 50, Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
  • Yeon Jong Huh
    Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Seungeun Lee
    Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
  • Sungwon Lee
    Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bldg. 10 Room 1C224D MSC 1182, Bethesda, MD 20892-1182.
  • Joon-Yong Jung
    Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea. messengr@catholic.ac.kr.
  • Hyun-Soo Lee
    Siemens Healthineers Ltd, Seoul, Republic of Korea.
  • Thomas Benkert
    Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Oberdürrbacher Strasse 6, 97080 Würzburg, Germany (J.F.H., S.V., C.M., L.M.P., T.A.B., H.K., A.M.W.); and Department of Application Development, Siemens Healthcare, Erlangen, Germany (T.B., J.P.).
  • Sung-Hong Park
    From the Graduate School of Medical Science and Engineering (K.H.K., S.H.P.) and Department of Bio and Brain Engineering (S.H.P.), Korea Advanced Institute of Science and Technology, Room 1002, CMS (E16) Building, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea; Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea (S.H.C.); Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea (S.H.C.); and Center for Nanoparticle Research, Institute for Basic Science, Seoul, Republic of Korea (S.H.C.).