Convolutional Neural Network for Differentiating Gastric Cancer from Gastritis Using Magnified Endoscopy with Narrow Band Imaging.

Journal: Digestive diseases and sciences
Published Date:

Abstract

BACKGROUND: Early detection of early gastric cancer (EGC) allows for less invasive cancer treatment. However, differentiating EGC from gastritis remains challenging. Although magnifying endoscopy with narrow band imaging (ME-NBI) is useful for differentiating EGC from gastritis, this skill takes substantial effort. Since the development of the ability to convolve the image while maintaining the characteristics of the input image (convolution neural network: CNN), allowing the classification of the input image (CNN system), the image recognition ability of CNN has dramatically improved.

Authors

  • Yusuke Horiuchi
    Department of Gastroenterology, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.
  • Kazuharu Aoyama
    AI Medical Service Inc Tokyo Japan.
  • Yoshitaka Tokai
  • Toshiaki Hirasawa
    Department of Gastroenterology, Cancer Institute Hospital Ariake, Japanese Foundation for Cancer Research, 3-10-6 Ariake, Koto-ku, Tokyo, 135-8550, Japan. toshiaki.hirasawa@jfcr.or.jp.
  • Shoichi Yoshimizu
    Department of Gastroenterology, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.
  • Akiyoshi Ishiyama
    Department of Gastroenterology, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.
  • Toshiyuki Yoshio
    Department of Gastroenterology, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan; Tada Tomohiro Institute of Gastroenterology and Proctology, Saitama, Japan.
  • Tomohiro Tsuchida
    Department of Gastroenterology, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.
  • Junko Fujisaki
    Department of Gastroenterology, Cancer Institute Hospital Ariake, Japanese Foundation for Cancer Research, 3-10-6 Ariake, Koto-ku, Tokyo, 135-8550, Japan.
  • Tomohiro Tada
    AI Medical Service Inc Tokyo Japan.