Vajravelu, Ashok and Tamil Selvan, K.S. and Abdul Jamila, Muhammad Mahadi and Jude, Anitha and Torre Diez, Isabel de la T (2023) Machine learning techniques to detect bleeding frame and area in wireless capsule endoscopy video. Journal of Intelligent & Fuzzy Systems, 44. pp. 353-364. ISSN 1064-1246
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Abstract
Wireless Capsule Endoscopy (WCE) allows direct visual inspecting of the full digestive system of the patient without invasion and pain, at the price of a long examination by physicians of a large number of photographs. This research presents a new approach to color extraction to differentiate bleeding frames from normal ones and locate more bleeding areas. We have a dual-system suggestion. We use entire color information on the WCE pictures and the pixel-represented clustering approach to get the clustered centers that characterize WCE pictures as words. Then we evaluate the status of a WCE framework using the nearby SVM and K methods (KNN). The classification performance is 95.75% accurate for the AUC 0.9771% and validates the exciting performance for bleeding classification provided by the suggested approach. Second, we present a two-step approach for extracting saliency maps to emphasize bleeding locations with a distinct color channel mixer to build a first-stage salience map. The second stage salience map was taken with optical contrast.We locate bleeding spots following a suitable fusion approach and threshold. Quantitative and qualitative studies demonstrate that our approaches can correctly distinguish bleeding sites from neighborhoods.
Item Type: | Article |
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Uncontrolled Keywords: | Bleeding classification and region detection, words-based color histograms, wireless capsule endoscopy |
Subjects: | R Medicine > R Medicine (General) > R855-855.5 Medical technology |
Divisions: | Faculty of Electrical and Electronic Engineering > Department of Electronic Enngineering |
Depositing User: | Mr. Mohamad Zulkhibri Rahmad |
Date Deposited: | 05 Apr 2023 03:17 |
Last Modified: | 05 Apr 2023 03:17 |
URI: | http://eprints.uthm.edu.my/id/eprint/8531 |
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