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A Neurofuzzy Methodology for the Diagnosis of Wireless-Capsule Endoscopic Images

  • Conference paper
Artificial Neural Networks: Biological Inspirations – ICANN 2005 (ICANN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3696))

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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.

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References

  1. Idden, G., Meran, G., Glukhovsky, A., Swain, P.: Wireless capsule endoscopy. Nature, 405–417 (2000)

    Google Scholar 

  2. Haralick, R.M.: Statistical and structural approaches to texture. IEEE Proc. 67, 786–804 (1979)

    Article  Google Scholar 

  3. Boulougoura, M., Wadge, E., Kodogiannis, V., Chowdrey, H.S.: Intelligent systems for computer-assisted clinical endoscopic image analysis. In: 2nd IASTED Int. Conf. on Biomedical Engineering, Innsbruck, Austria, pp. 405–408 (2004)

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  4. Kuncheva, L.I.: Fuzzy Classifier Design. Physica-Verlag, Heidelberg (2000)

    MATH  Google Scholar 

  5. Wadge, E., Kodogiannis, V.S.: Intelligent diagnosis of UTI in vivo using gas sensor arrays. In: Int. Conf. on Neural Networks and Expert Systems in Medicine and HealthCare, NNESMED 2003, pp. 93–98 (2003)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Mechatronics Group, School of Computer Science, University of Westminster, London, HA1 3TP, UK

    Vassilis Kodogiannis

  2. Biomedical Sciences Dept, School of Biosciences, University of Westminster, London, W1W 6UW, UK

    H. S. Chowdrey

Authors
  1. Vassilis Kodogiannis
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  2. H. S. Chowdrey
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Editor information

Editors and Affiliations

  1. Department of Informatics, Nicolaus Copernicus University, Toruń, Poland

    Włodzisław Duch

  2. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01–447, Warsaw, Poland

    Janusz Kacprzyk

  3. Adaptive Informatics Research Centre, Helsinki University of Technology, P.O. Box 5400, 02015 HUT, Finland

    Erkki Oja

  4. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Sławomir Zadrożny

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© 2005 Springer-Verlag Berlin Heidelberg

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Kodogiannis, V., Chowdrey, H.S. (2005). A Neurofuzzy Methodology for the Diagnosis of Wireless-Capsule Endoscopic Images. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Biological Inspirations – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550822_100

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  • DOI: https://doi.org/10.1007/11550822_100

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28752-0

  • Online ISBN: 978-3-540-28754-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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