Artificial intelligence and computer-aided diagnosis for colonoscopy: where do we stand now?

Shin-Ei Kudo; Yuichi Mori; Usama M Abdel-Aal; Masashi Misawa; Hayato Itoh; Masahiro Oda; Kensaku Mori

doi:10.21037/tgh.2019.12.14

Artificial intelligence and computer-aided diagnosis for colonoscopy: where do we stand now?

Transl Gastroenterol Hepatol. 2021 Oct 25:6:64. doi: 10.21037/tgh.2019.12.14. eCollection 2021.

Authors

Shin-Ei Kudo¹, Yuichi Mori¹, Usama M Abdel-Aal^{1

2}, Masashi Misawa¹, Hayato Itoh³, Masahiro Oda³, Kensaku Mori³

Affiliations

¹ Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan.
² Internal Medicine, Faculty of Medicine, Sohag University, Sohag, Egypt.
³ Graduate School of Informatics, Nagoya University, Nagoya, Japan.

Abstract

Computer-aided diagnosis (CAD) for colonoscopy with use of artificial intelligence (AI) is catching increased attention of endoscopists. CAD allows automated detection and pathological prediction, namely optical biopsy, of colorectal polyps during real-time endoscopy, which help endoscopists avoid missing and/or misdiagnosing colorectal lesions. With the increased number of publications in this field and emergence of the AI medical device that have already secured regulatory approval, CAD in colonoscopy is now being implemented into clinical practice. On the other side, drawbacks and weak points of CAD in colonoscopy have not been thoroughly discussed. In this review, we provide an overview of CAD for optical biopsy of colorectal lesions with a particular focus on its clinical applications and limitations.

Keywords: Computer-aided diagnosis (CAD); colon cancer; polyp.

Publication types

Review