Wireless Capsule Endoscopy : A New Tool for Cancer Screening in the Colon With Deep-Learning-Based Polyp Recognition

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

54 Scopus Citations
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Original languageEnglish
Journal / PublicationProceedings of the IEEE
Volume108
Issue number1
Online published18 Nov 2019
Publication statusPublished - Jan 2020

Abstract

Accurate recognition of polyps is crucial for early colorectal cancer diagnosis and treatment. Wireless capsule endoscopy (WCE) is a noninvasive, wireless imaging tool that allows direct visualization of the entire colon without discomfort to patients and has the potential to revolutionize the screening workup for colorectal diseases. However, current manual review is laborious and time consuming, requiring the undivided concentration of the gastroenterologist. Computational methods that can assist automated polyp recognition will enhance the outcome both in terms of diagnostic accuracy and efficiency of WCE. This review introduces the computer-assisted algorithms as applied to colorectal polyp screening, focusing on the successes of deep-learning-based strategies in the WCE sequences. We survey key applications of WCE polyp recognition, covering deep-learning-based image-level classification, lesion region detection, and pixel-accurate segmentation. We conclude by discussing emerging research challenges, possible trends, and future directions.

Research Area(s)

  • Cancer screening, deep learning, polyp recognition, wireless capsule endoscopy (WCE)