A neurofuzzy methodology for the diagnosis of wireless-capsule endoscopic images

  • Authors:
  • Vassilis Kodogiannis;H. S. Chowdrey

  • Affiliations:
  • Mechatronics Group, School of Computer Science, University of Westminster, London, UK;Biomedical Sciences Dept, School of Biosciences, University of Westminster, London, UK

  • Venue:
  • ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
  • Year:
  • 2005

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Abstract

In this paper, a detection system to support medical diagnosis and detection of abnormal lesions by processing endoscopic images is presented. The endoscopic images possess rich information expressed by texture. Schemes have been developed to extract new texture features from the texture spectra in the chromatic and achromatic domains for a selected region of interest from each colour component histogram of images acquired by the new M2A Swallowable Capsule. The implementation of an advanced fuzzy inference neural network which combines fuzzy systems and clustering schemes and the concept of fusion of multiple classifiers dedicated to specific feature parameters have been also adopted in this paper. The preliminary test results support the feasibility of the proposed method.