Novel computer-assisted diagnosis system for endoscopic disease activity in patients with ulcerative colitis.

Journal: Gastrointestinal endoscopy
Published Date: Feb 1, 2019

Abstract

BACKGROUND AND AIMS: Evaluation of endoscopic disease activity for patients with ulcerative colitis (UC) is important when determining the treatment of choice. However, endoscopists require a certain period of training to evaluate the activity of inflammation properly, and interobserver variability exists. Therefore, we constructed a computer-assisted diagnosis (CAD) system using a convolutional neural network (CNN) and evaluated its performance using a large dataset of endoscopic images from patients with UC.

Authors

  • Tsuyoshi Ozawa
    Tada Tomohiro Institute of Gastroenterology and Proctology, Saitama, Japan.
  • Soichiro Ishihara
    Tada Tomohiro Institute of Gastroenterology and Proctology, Saitama, Japan; Surgery Department, Sanno Hospital, International University of Health and Welfare, Tokyo, Japan; Department of Surgical Oncology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Mitsuhiro Fujishiro
    Department of Gastroenterology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan; Department of Endoscopy and Endoscopic Surgery, The University of Tokyo, Tokyo, Japan.
  • Hiroaki Saito
    Department of Gastroenterology, Sendai Kousei Hospital, Miyagi, Japan.
  • Youichi Kumagai
    Department of Digestive Tract and General Surgery, Saitama Medical Center, Saitama Medical University, Saitama, Japan.
  • Satoki Shichijo
    Department of Gastrointestinal Oncology Osaka International Cancer Institute Osaka Japan.
  • Kazuharu Aoyama
    AI Medical Service Inc Tokyo Japan.
  • Tomohiro Tada
    AI Medical Service Inc Tokyo Japan.

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