A systematic review of ulcer detection methods in wireless capsule endoscopy

Abstract

Background

Ulcers are one of the most prevalent disorders in the gastrointestinal (GI) tract, affecting many people worldwide. Wireless capsule endoscopy (WCE) emerges as the most non-invasive way to diagnose ulcers in the GI tract. However, manually reviewing images captured by WCE is a tedious and time-consuming process. Implementing a computer-aided ulcer detection system can facilitate the automatic evaluation of these images.

Methods

Many researchers have proposed various models to develop automatic ulcer detection methods. This research aims to conduct a systematic review by scouring four repositories (Scopus, PubMed, IEEE Xplore, and ScienceDirect) for all original publications on computer-aided ulcer detection published between 2011 and 2024. The review follows the the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines.

Results

The full texts of 89 scientific articles were reviewed. The contributions of this paper are two-fold: I) it reports and summarizes the current state-of-the-art ulcer detection algorithms; and II) it finds the most appropriate and preferable method in terms of color space, region of interest selection, feature extraction, and classifier.

Conclusion

The paper concludes with a discussion of the challenges and futuredirections for ulcer detection.