A systematic review of ulcer detection methods in wireless capsule endoscopy
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 an...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-01-01
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| Series: | Informatics in Medicine Unlocked |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352914824001576 |
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| Summary: | 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. |
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| ISSN: | 2352-9148 |