WestminsterResearch

Neuro-fuzzy classification system for wireless-capsule endoscopic images

Kodogiannis, Vassilis and Lygouras, John N. (2008) Neuro-fuzzy classification system for wireless-capsule endoscopic images. International Journal of Electrical, Computer, and Systems Engineering, 2 (1). pp. 55-63. ISSN 1307-5179

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Official URL: http://www.waset.org/journals/ijeee/v2/v2-1-8.pdf

Abstract

In this research study, an intelligent detection system to support medical diagnosis and detection of abnormal lesions by processing endoscopic images is presented. The images used in this study have been obtained using the M2A Swallowable Imaging Capsule - a patented, video color-imaging disposable capsule. Schemes have been developed to extract texture features from the fuzzy texture spectra in the chromatic and achromatic domains for a selected region of interest from each color component histogram of endoscopic images. The implementation of an advanced fuzzy inference neural network which combines fuzzy systems and artificial neural networks and the concept of fusion of multiple classifiers dedicated to specific feature parameters have been also adopted in this paper. The achieved high detection accuracy of the proposed system has provided thus an indication that such intelligent schemes could be used as a supplementary diagnostic tool in endoscopy.

Item Type:Article
Research Community:University of Westminster > Electronics and Computer Science, School of
ID Code:8740
Deposited On:26 Oct 2010 15:43
Last Modified:26 Oct 2010 15:43

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