[Development of a Deep Learning Model for Judging Late Gadolinium-enhancement in Cardiac MRI].

Journal: Nihon Hoshasen Gijutsu Gakkai zasshi
PMID: 38897968

Abstract

PURPOSE: To verify the usefulness of a deep learning model for determining the presence or absence of contrast-enhanced myocardium in late gadolinium-enhancement images in cardiac MRI.

Authors

  • Akihiro Kasahara
    Radiology Center, The University of Tokyo Hospital, Tokyo, Japan.
  • Takahiro Iwasaki
    Kyushu University.
  • Takuya Mizutani
    Graduate Division of Health Sciences, Komazawa University, Tokyo, Japan.
  • Tsuyoshi Ueyama
    Radiology Center, The University of Tokyo Hospital, Tokyo, Japan.
  • Yoshiharu Sekine
    Radiology Center, The University of Tokyo Hospital.
  • Masae Uehara
    Department of Cardiovascular Medicine, The University of Tokyo Hospital.
  • Satoshi Kodera
    Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo.
  • Wataru Gonoi
    Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Hideyuki Iwanaga
    Radiology Center, The University of Tokyo Hospital, Tokyo, Japan.
  • Osamu Abe
    From the Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan 113-8655.

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