Synthetic temporal bone CT generation from UTE-MRI using a cycleGAN-based deep learning model: advancing beyond CT-MR imaging fusion.

Journal: European radiology
PMID:

Abstract

OBJECTIVES: The aim of this study is to develop a deep-learning model to create synthetic temporal bone computed tomography (CT) images from ultrashort echo-time magnetic resonance imaging (MRI) scans, thereby addressing the intrinsic limitations of MRI in localizing anatomic landmarks in temporal bone CT.

Authors

  • Sung-Hye You
    From the Graduate School of Medical Science and Engineering, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea (K.S.C., B.J.); Department of Radiology, Korea University College of Medicine, Anam Hospital, Seoul, Republic of Korea (S.H.Y.); Bio Imaging and Signal Processing Laboratory, Department of Bio and Brain Engineering, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea (Y.H., J.C.Y.); Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul 110-744, Republic of Korea (S.H.C.); Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea (S.H.C.); Center for Nanoparticle Research, Institute for Basic Science (IBS), Seoul, Republic of Korea (S.H.C.); KAIST Institute for Health Science and Technology, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea (B.J.); and KAIST Institute for Artificial Intelligence, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea (B.J.).
  • Yongwon Cho
    Department of Convergence Medicine, Asan Medical Center, College of Medicine, University of Ulsan, 88, Olympic-ro 43-gil, Seoul, 05505, South Korea.
  • Byungjun Kim
    Department of Radiology, Korea University Anam Hospital, Seoul, Korea.
  • Jeeho Kim
    Department of Data Science, Korea University College of Informatics, Seoul, Korea.
  • Gi Jung Im
  • Euyhyun Park
  • InSeong Kim
    Siemens Healthineers (I.K.), Seoul, Korea.
  • Kyung Min Kim
    Hewlett Packard Labs, Palo Alto, CA, 94304, USA.
  • Bo Kyu Kim
    From the Department of Radiology, (S.-H.Y., B.K., B.K.K., A.P., S.E.P.), Anam Hospital, Korea University College of Medicine, Seoul, Korea.