Deep-learning 2.5-dimensional single-shot detector improves the performance of automated detection of brain metastases on contrast-enhanced CT.

Journal: Neuroradiology
Published Date: Jan 22, 2022

Abstract

PURPOSE: This study aims to develop a 2.5-dimensional (2.5D) deep-learning, object detection model for the automated detection of brain metastases, into which three consecutive slices were fed as the input for the prediction in the central slice, and to compare its performance with that of an ordinary 2-dimensional (2D) model.

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.

Keywords

External Resources

Popular Topics
Recent Journals