Classification of large-scale image database of various skin diseases using deep learning.

Journal: International journal of computer assisted radiology and surgery
Published Date: Jul 26, 2021

Abstract

PURPOSE: The purpose of this study was to develop a deep learning-based computer-aided diagnosis system for skin disease classification using photographic images of patients. The targets are 59 skin diseases, including localized and diffuse diseases captured by photographic cameras, resulting in highly diverse images in terms of the appearance of the diseases or photographic conditions.

Authors

  • Masaya Tanaka
    Institute of Engineering, Tokyo University of Agriculture and Technology, Koganei, Tokyo, Japan.
  • Atsushi Saito
    Institute of Engineering, Tokyo University of Agriculture and Technology, Koganei, Tokyo, Japan.
  • Kosuke Shido
    Department of Dermatology, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan.
  • Yasuhiro Fujisawa
    Dept. of Dermatology, University of Tsukuba.
  • Kenshi Yamasaki
    Department of Dermatology, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan.
  • Manabu Fujimoto
    Department of Dermatology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
  • Kohei Murao
    Research Centre for Medical Bigdata, National Institute of Informatics, Chiyoda-ku, Tokyo, Japan.
  • Youichirou Ninomiya
    Research Centre for Medical Bigdata, National Institute of Informatics, Chiyoda-ku, Tokyo, Japan.
  • Shin'ichi Satoh
    Research Center for Medical Bigdata (RCMB), National Institute of Informatics, Tokyo, Japan.
  • Akinobu Shimizu
    Institute of Engineering, Tokyo University of Agriculture and Technology, Koganei, Tokyo, Japan. simiz@cc.tuat.ac.jp.

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