Optimum colour space selection for ulcerated regions using statistical analysis and classification of ulcerated frames from WCE video footage

Suman, S. and Walter, N. and Hussin, F.A. and Malik, A.S. and Ho, S.H. and Goh, K.L. and Hilmi, I. (2015) Optimum colour space selection for ulcerated regions using statistical analysis and classification of ulcerated frames from WCE video footage. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9489. pp. 373-381. ISSN 03029743

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Abstract

The Wireless Capsule Endoscopy (WCE) is a painless and non-invasive procedure that allows clinicians to visualize the entire Gastrointestinal Tract (GIT) and detect various abnormalities. During the inspection of GIT, numerous images are acquired at a rate of approximately 2 frames per second (fps) and recorded into a video footage (containing about 55,000 images). Inspecting the WCE video is very tedious and time consuming for the doctors, resulting in limited application of WCE. Therefore, it is crucial to develop a computer aided intelligent algorithm to process the huge number of WCE frames. This paper proposes an ulcerated frame detection method based on RGB and CIE Lab colour spaces. In order to select and provide the classifier with the bands containing most ulcer information, a statistical analysis of ulcerated images pixel based is proposed. The resulting band selection will enhance the classification results and increase the sensitivity and specificity with regards to ulcerated frame identification. © Springer International Publishing Switzerland 2015.

Item Type: Article
Additional Information: cited By 2; Conference of 22nd International Conference on Neural Information Processing, ICONIP 2015 ; Conference Date: 9 November 2015 Through 12 November 2015; Conference Code:157859
Uncontrolled Keywords: Classification (of information); Color; Dermatology; Diseases; Endoscopy; Image analysis; Image processing; Information science; Noninvasive medical procedures, Classification results; Colour spaces; Frame detection; Frames per seconds; Gastrointestinal tract; Intelligent Algorithms; Sensitivity and specificity; Wireless capsule endoscopy, Statistical methods
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 16:17
Last Modified: 09 Nov 2023 16:17
URI: https://khub.utp.edu.my/scholars/id/eprint/6172

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