Effects of deep learning on radiologists' and radiology residents' performance in identifying esophageal cancer on CT.

Journal: The British journal of radiology
Published Date: Apr 22, 2023

Abstract

OBJECTIVE: To investigate the effectiveness of a deep learning model in helping radiologists or radiology residents detect esophageal cancer on contrast-enhanced CT images.

Authors

  • Koichiro Yasaka
    From the Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan 113-8655.
  • Sosuke Hatano
    Department of Radiology, The University of Tokyo Hospital, Tokyo, Japan.
  • Masumi Mizuki
    Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
  • Naomasa Okimoto
  • Takatoshi Kubo
    Department of Radiology, The University of Tokyo Hospital, Tokyo, Japan.
  • Eisuke Shibata
    Department of Radiology, The University of Tokyo Hospital, Tokyo, Japan.
  • Takeyuki Watadani
    Department of Radiology, Faculty of Medicine, The University of Tokyo.
  • Osamu Abe
    From the Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan 113-8655.

Keywords

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