[Automatic Quantification of Breast Density from Mammography Using Deep Learning].

Journal: Nihon Hoshasen Gijutsu Gakkai zasshi
Published Date: Jan 1, 2021

Abstract

BACKGROUND: In the field of breast screening using mammography, announcing to the examinees whether they are dense or not has not been deprecated in Japan. One of the reasons is a shortage of objectivity estimating their dense breast. Our aim is to build a system with deep learning algorithm to calculate and quantify objective breast density automatically.

Authors

  • Kenichi Inoue
    Breast Cancer Center, Shonan Memorial Hospital, Kanagawa.
  • Aika Kawasaki
    Shonan Memorial Hospital, Breast Cancer Center.
  • Kanako Koshimizu
    Shonan Memorial Hospital, Breast Cancer Center.
  • Chigusa Ariizumi
    Shonan Memorial Hospital, Breast Cancer Center.
  • Keiko Unno
    Shonan Memorial Hospital, Breast Cancer Center.
  • Miki Nagashima
    Shonan Memorial Hospital, Breast Cancer Center.
  • Kayo Mizuno
    Shonan Memorial Hospital, Breast Cancer Center.
  • Misono Misumi
    Shonan Memorial Hospital, Breast Cancer Center.
  • Chizuko Tsutsumi
    Shonan Memorial Hospital, Breast Cancer Center.
  • Takeshi Sasaki
    Department of Next-Generation Pathology Information Networking, Faculty of Medicine, The University of Tokyo.
  • Takako Doi
    Shonan Memorial Hospital, Breast Cancer Center.

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