A neuro-fuzzy-based system for detecting abnormal patterns in wireless-capsule endoscopic images

被引：32
作者：
Kodogiannis, V. S. [1 ]
Boulougoura, M.
Lygouras, J. N.
Petrounias, I.
机构：
[1] Univ Westminster, Sch Comp Sci, Ctr Syst Anal, London HA1 3TP, England
[2] Siemens SA, Dev Innovat & Projects SWC Commun Syst, GR-14564 Athens, Greece
[3] Democritus Univ Thrace, Dept Elect & Comp Engn, GR-67100 Xanthi, Greece
[4] Univ Manchester, Sch Informat, Manchester M60 1QD, Lancs, England
来源：
NEUROCOMPUTING | 2007年 / 70卷 / 4-6期
关键词：
medical imaging; computer-aided diagnosis; endoscopy; neuro-fuzzy networks; fuzzy integral;
D O I：
10.1016/j.neucom.2006.10.024
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Wireless capsule endoscopy (WCE) constitutes a recent technology in which a capsule with micro-camera attached to it, is swallowed by the patient. This paper presents an integrated methodology for detecting abnormal patterns in WCE images. Two issues are being addressed, including the extraction of texture features from the texture spectra in the chromatic and achromatic domains from each colour component histogram of WCE images and the concept of a fusion of multiple classifiers. The implementation of an advanced neuro-fuzzy learning scheme has been also adopted in this paper. The high detection accuracy of the proposed system provides thus an indication that such intelligent schemes could be used as a supplementary diagnostic tool in WCE. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码：704 / 717
页数：14
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