Deep-learning single-shot detector for automatic detection of brain metastases with the combined use of contrast-enhanced and non-enhanced computed tomography images.

Journal: European journal of radiology
Published Date: Nov 1, 2021

Abstract

PURPOSE: To develop a deep-learning object detection model for automatic detection of brain metastases that simultaneously uses contrast-enhanced and non-enhanced images as inputs, and to compare its performance with that of a model that uses only contrast-enhanced images.

Authors

  • Hidemasa Takao
    Department of Radiology, Graduate School of Medicine, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
  • Shiori Amemiya
  • Shimpei Kato
    Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Hiroshi Yamashita
    Department of Radiology, Graduate School of Medicine, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
  • Naoya Sakamoto
    Department of Gastroenterology and Hepatology, Hokkaido University Graduate School of Medicine, Sapporo 0608638, 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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