Commenced in January 2007
Paper Count: 30578
Neuro-fuzzy Classification System for Wireless-Capsule Endoscopic Images
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.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1073581Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1401
 K. Nagasako, T. Fujimori, Y. Hoshihara, M. Tabuchi, 1998. Atlas of Gastroenterologic Endoscopy by High-resolution Video-Endoscopy, IGAKU-SHOIN Ltd., Tokyo
 S. Krishnan, P. Wang, C. Kugean, M. Tjoa, "Classification of endoscopic images based on texture and neural network", Proc. 23rd Annual IEEE Int. Conf. in Engineering in Medicine and Biology, (4), pp. 3691-3695, 2001
 D.E. Maroulis, D.K. Iakovidis, S.A. Karkanis, D.A. Karras, "CoLD: a versatile detection system for colorectal lesions endoscopy videoframes", Computer Methods and Programs in Biomedicine, (70), pp. 151-166, 2003
 A.F. Ravens, C.P. Swain, "The wireless capsule: new light in the darkness", in Digestive Diseases, vol. 20, pp. 127-133, 2002.
 G. Idden, G. Meran, A. Glukhovsky anÔé¼d P. Swain, "Wireless capsule endoscopy", Nature, pp. 405-417, 2000
 M. Mylonaki, A. Fritscher-Ravens, C.P. Swain, "Clinical results of wireless capsule endoscopy" Gastrointest. Endosc., vol.55, AB146, 2002
 P. Spyridonos, F. Vilari├▒o, J. Vitri├á and P. Radeva, "Identification of Intestinal Motility Events of Capsule Endoscopy Video Analysis", Proc. of Advanced Concepts for Intelligent Vision Systems Conf, Antwerp, Belgium, pp. 575-580, 2005
 F. Vilari├▒o, P. Spyridonos, J. Vitri├á, P. Radeva, "Self Organized Maps for Intestinal Contractions Categorization with Wireless Capsule Video Endoscopy", Proc. of the 3rd European Medical and Biological Engineering Conference, EMBEC'05 Prague, pp. 3443-3447, 2005.
 N. Bourbakis, S. Makrogiannis, D. Kavraki, "A Neural Network-based Detection of Bleeding in sequences of WCE images", Proc. of the 5th IEEE Symposium on Bioinformatics and Bioengineering (BIBE-05), pp. 324-327, 2005
 P.Y Lau, P.L. Correia, "Detection of bleeding patterns in WCE video using multiple features", Engineering in Medicine and Biology Society, EMBS 2007, 29th Annual International Conference of the IEEE, pp. 5601-5604, 2007
 M.T. Coimbra, J.P.S. Cunha, "MPEG-7 Visual Descriptors- Contributions for Automated Feature Extraction in Capsule Endoscopy", IEEE transactions on circuits and systems for video technology, Vol. 16, No. 5, pp. 628-637, 2006.
 M. Gletsos, S. Mougiakakou, G. Matsopoulos, K. Nikita, A. Nikita, D. Kelekis, "A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier", IEEE Trans. on Information Technology in Biomedicine, Vol. 7, No. 3, pp. 153-162, 2003.
 D-C He, L. Wang, "Texture features based on texture spectrum", Pattern Recognition, Vol. 24, No. 5, pp. 391-399, 1991.
 M. Boulougoura, E. Wadge, V.S. Kodogiannis, H.S. Chowdrey, "Intelligent systems for computer-assisted clinical endoscopic image analysis", 2nd IASTED Int. Conf. on Biomedical Engineering, Innsbruck, Austria, pp. 405-408, 2004.
 V.S. Kodogiannis, M. Boulougoura, E. Wadge, J.N. Lygouras, "The usage of soft-computing methodologies in interpreting capsule endoscopy", Engineering Applications in Artificial Intelligence, Elsevier 2007, Vol. 20, pp. 539-553.
 R. Haralick, "Statistical and structural approaches to texture", IEEE Proc, Vol. 67, pp. 786- 804, 1979
 A. Barcelo, E. Montseny, P. Sobrevilla, Fuzzy Texture Unit and Fuzzy Texture Spectrum for texture characterization, Fuzzy Sets and Systems, Vol. 158, pp. 239 - 252, 2007
 V.S. Kodogiannis, "Intelligent classification of bacterial clinical isolates in vitro, using an array of gas sensors", J. Intelligent and Fuzzy systems, Vol. 16, No. 1, pp. 1-14, 2005
 Sugeno, M. "Fuzzy measures and fuzzy integrals: a survey, in Fuzzy Automata and Decision Processes", (M.M. Gupta, G. N. Saridis, and B.R. Gaines, editors), pp. 89-102, North-Holland, 1977
 R. Yager, "A General Approach to Criteria Aggregation using Fuzzy Measures", International Journal of Man-Machine Studies, Vol. 39, No. 2, pp. 187-213, 1993.
 M. Grabisch, T. Murofushi, M. Sugeno, M., "Fuzzy measure of fuzzy events defined by fuzzy integrals", Fuzzy Sets and Systems, Vol. 50, pp. 293-313, 1992
 S. Mitra, S.K. Pal, P. Mitra, "Data mining in soft computing framework: A survey", IEEE Transactions on Neural Networks, Vol. 13, No. 1, pp. 3-14, 2000
 L.I Kuncheva, Fuzzy Classifier Design, Physica-Verlag, 2000
 C.T. Teng Lin, C.S. George Lee, Neural Fuzzy Systems, Prentice Hall, 1996
 V. Kodogiannis, "Computer-aided Diagnosis in Clinical Endoscopy using Neuro-Fuzzy System", in Proceedings of IEEE FUZZ 2004, pp. 1425-1429, 2004