Establishment and validation of a computer-assisted colonic polyp localization system based on deep learning.

ABSTRACT:

Background

Artificial intelligence in colonoscopy is an emerging field, and its application may help colonoscopists improve inspection quality and reduce the rate of missed polyps and adenomas. Several deep learning-based computer-assisted detection (CADe) techniques were established from small single-center datasets, and unrepresentative learning materials might confine their application and generalization in wide practice. Although CADes have been reported to identify polyps in colonoscopic images and videos in real time, their diagnostic performance deserves to be further validated in clinical practice.

Aim

To train and test a CADe based on multicenter high-quality images of polyps and preliminarily validate it in clinical colonoscopies.

Methods

With high-quality s

SUBMITTER: Zhao SB 

PROVIDER: S-EPMC8384745 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature