Computer-Aided Diagnosis Based on Convolutional Neural Network System for Colorectal Polyp Classification: Preliminary Experience.

Journal: Oncology
Published Date:

Abstract

BACKGROUND AND AIM: Computer-aided diagnosis (CAD) is becoming a next-generation tool for the diagnosis of human disease. CAD for colon polyps has been suggested as a particularly useful tool for trainee colonoscopists, as the use of a CAD system avoids the complications associated with endoscopic resections. In addition to conventional CAD, a convolutional neural network (CNN) system utilizing artificial intelligence (AI) has been developing rapidly over the past 5 years. We attempted to generate a unique CNN-CAD system with an AI function that studied endoscopic images extracted from movies obtained with colonoscopes used in routine examinations. Here, we report our preliminary results of this novel CNN-CAD system for the diagnosis of colon polyps.

Authors

  • Yoriaki Komeda
    Department of Gastroenterology and Hepatology, Kindai University Faculty of Medicine, Osaka-Sayama, Japan.
  • Hisashi Handa
  • Tomohiro Watanabe
  • Takanobu Nomura
    Medical Affairs, Kyowa Kirin Co. Ltd, Tokyo, Japan.
  • Misaki Kitahashi
  • Toshiharu Sakurai
  • Ayana Okamoto
  • Tomohiro Minami
  • Masashi Kono
  • Tadaaki Arizumi
  • Mamoru Takenaka
  • Satoru Hagiwara
  • Shigenaga Matsui
  • Naoshi Nishida
  • Hiroshi Kashida
  • Masatoshi Kudo