@article{(Open Science Index):https://publications.waset.org/pdf/9862,
	  title     = {Neuro-fuzzy Classification System for Wireless-Capsule Endoscopic Images},
	  author    = {Vassilis S. Kodogiannis and  John N. Lygouras},
	  country	= {},
	  institution	= {},
	  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.},
	    journal   = {International Journal of Electrical and Computer Engineering},
	  volume    = {2},
	  number    = {9},
	  year      = {2008},
	  pages     = {1908 - 1916},
	  ee        = {https://publications.waset.org/pdf/9862},
	  url   	= {https://publications.waset.org/vol/21},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 21, 2008},
	}