Intelligent systems for the diagnosis of wireless-capsule endoscopic images

  • Authors:
  • V. Kodogiannis;M. Boulougoura;E. Wadge

  • Affiliations:
  • Mechatronics Group, Computer Science Department, University of Westminster, London, United Kingdom;Mechatronics Group, Computer Science Department, University of Westminster, London, United Kingdom;Mechatronics Group, Computer Science Department, University of Westminster, London, United Kingdom

  • Venue:
  • SSIP'05 Proceedings of the 5th WSEAS international conference on Signal, speech and image processing
  • Year:
  • 2005

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Abstract

Intelligent computerised systems can provide useful assistance to the physician in the rapid identification of tissue abnormalities and accurate diagnosis in real-time. The endoscopic images possess rich information expressed by texture. In this paper schemes have been developed to extract texture features from the texture spectra in the chromatic and achromatic domains for a selected region of interest from each colour component histogram of endoscopic images acquired by the new M2A Swallowable Capsule. The implementation of advanced learning-based schemes and the concept of fusion of multiple classifiers have been also adopted in this paper. The test results support the feasibility of the proposed methodology for this type of endoscopic images.