Quick and accurate selection of hand images among radiographs from various body parts using deep learning.

Journal: Journal of X-ray science and technology
Published Date: Jan 1, 2020

Abstract

BACKGROUND: Although rheumatoid arthritis (RA) causes destruction of articular cartilage, early treatment significantly improves symptoms and delays progression. It is important to detect subtle damage for an early diagnosis. Recent software programs are comparable with the conventional human scoring method regarding detectability of the radiographic progression of RA. Thus, automatic and accurate selection of relevant images (e.g. hand images) among radiographic images of various body parts is necessary for serial analysis on a large scale.

Authors

  • Kohei Fujiwara
    Department of Health Sciences, Hokkaido University, Kita-ku, Sapporo, Japan.
  • Wanxuan Fang
    Faculty of Health Sciences, Hokkaido University, Kita-ku, Sapporo, Japan.
  • Taichi Okino
    Graduate School of Health Sciences, Hokkaido University, Kita-ku, Sapporo, Japan.
  • Kenneth Sutherland
    Global Center for Biomedical Science and Engineering, Hokkaido University, Kita-ku, Sapporo, Japan.
  • Akira Furusaki
    Sagawa Akira Rheumatology Clinic, Chuo-ku, Sapporo, Japan.
  • Akira Sagawa
    Sagawa Akira Rheumatology Clinic, Chuo-ku, Sapporo, Japan.
  • Tamotsu Kamishima
    Faculty of Health Sciences, Hokkaido University, Kita-ku, Sapporo, Japan.

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