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Published in:
2010 | OriginalPaper | Chapter
Automated Recognition of Abnormal Structures in WCE Images Based on Texture Most Discriminative Descriptors
Authors : Piotr Szczypiński, Artur Klepaczko
Published in: Image Processing and Communications Challenges 2
Publisher: Springer Berlin Heidelberg
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In this paper we study the problem of classification of wireless capsule endoscopy images (WCE). We aim at developing a computer system that would aid in medical diagnosis procedure. The goal is to automatically detect images showing pathological alterations in an 8-hour-long WCE video. We focus on three classes of pathologies, ulcers, bleedings and petechia, since they are typical for several diseases of intestines. Utilized are methods for image texture and color analysis to obtain numerical description of images. Then, three methods for selection of most discriminative descriptors are used, namely Vector Supported Convex Hull, Support Vector Machines and Radial Basis Function Networks. The results produced by the three methods are compared.