Automated histological classification of whole-slide images of gastric biopsy specimens.

Journal: Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Published Date: Jun 2, 2017

Abstract

BACKGROUND: Automated image analysis has been developed currently in the field of surgical pathology. The aim of the present study was to evaluate the classification accuracy of the e-Pathologist image analysis software.

Authors

  • Hiroshi Yoshida
    Division of Pathology and Clinical Laboratories, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan. hiroyosh@ncc.go.jp.
  • Taichi Shimazu
    Epidemiology and Prevention Group, Center for Public Health Sciences, National Cancer Center, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
  • Tomoharu Kiyuna
    Medical Solutions Division, NEC Corporation, 5-7-1 Shiba, Minato-ku, Tokyo, 108-8001, Japan.
  • Atsushi Marugame
    Space System Division, NEC Corporation, 10, Nisshin-cho 1-Chome, Fuchu, Tokyo, 183-8501, Japan.
  • Yoshiko Yamashita
    Medical Solutions Division, NEC Corporation, 5-7-1 Shiba, Minato-ku, Tokyo, 108-8001, Japan.
  • Eric Cosatto
    Department of Machine Learning, NEC Laboratories America, NJ, USA.
  • Hirokazu Taniguchi
  • Shigeki Sekine
    Division of Pathology and Clinical Laboratories, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
  • Atsushi Ochiai
    Division of Pathology and Clinical Laboratories, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.

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