Skip to main content

An Intelligent Decision Support System in Wireless-Capsule Endoscopy

  • Chapter
Intelligent Techniques and Tools for Novel System Architectures

Part of the book series: Studies in Computational Intelligence ((SCI,volume 109))

Summary

In this chapter, 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 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 Swallow-able Capsule. The implementation of advanced neural learning-based schemes and the concept of fusion of multiple classifiers dedicated to specific feature parameters have been also adopted in this chapter. The test results support the feasibility of the proposed methodology.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Economou, G.P.K., Lymberopoulos, D., Karvatselou, E., Chassomeris, C.: A new concept toward computer-aided medical diagnosis – A prototype implementation addressing pulmonary diseases, IEEE Transactions on Information Technology in Biomedicine, 5 (1) 55–61 (2001)

    Article  Google Scholar 

  2. Kovalerchuk, B., Vityaev, E., Ruiz, J.F.: Consistent knowledge discovery in medical; diagnosis, IEEE Engineering in Medicine and Biology Magazine, 19 (4) 26–37 (2000)

    Article  Google Scholar 

  3. West, D., West, V.: Model selection for a medical diagnostic decision support system: A Breast cancer detection case, Artificial Intelligence in Medicine, 20 (3) 183–204 (2000)

    Article  Google Scholar 

  4. Haga, Y., Esashi, M.: Biomedical microsystems for minimally invasive diagnosis and treatment, Proceedings of IEEE, 92 98–114 (2004)

    Article  Google Scholar 

  5. Krishnan, S., Wang, P., Kugean, C., Tjoa, M.: Classification of endoscopic images based on texture and neural network, Proceedings of 23rd Annual IEEE International Conference in Engineering in Medicine and Biology, 4 3691–3695 (2001)

    Google Scholar 

  6. Maroulis, D.E., Iakovidis, D.K., Karkanis, S.A, Karras, D.A.: CoLD: A versatile detection system for colorectal lesions endoscopy video-frames, Computer Methods and Programs in Biomedicine, 70 151–166 (2003)

    Article  Google Scholar 

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

    Google Scholar 

  8. Gletsos, M., Mougiakakou, S., Matsopoulos, G., Nikita, K., Nikita, A., Kelekis, D.: A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier, IEEE Transactions on Information Technology in Biomedicine, 7 (3) 153–162 (2003)

    Article  Google Scholar 

  9. Wadge, E., Boulougoura, N., Kodogiannis, V.: Computer-assisted diagnosis of wireless-capsule endoscopic images using neural network based techniques, Proceedings of the 2005 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, CIMSA, 328–333 (2005)

    Google Scholar 

  10. Kodogiannis, V., Boulougoura, M., Wadge, E.: An intelligent system for diagnosis of capsule endoscopic images, Proceedings of the second International Conference on Computational Intelligence in Medicine and Healthcare (CIMED 2005), Portugal, 340–347 (2005)

    Google Scholar 

  11. Kodogiannis, V.: Computer-aided diagnosis in clinical endoscopy using neuro-Fuzzy system, IEEE FUZZ 2004, 1425–1429 (2004)

    Google Scholar 

  12. Boulougoura, M., Wadge, E., Kodogiannis, V., Chowdrey, H.S.: Intelligent systems for computer-assisted clinical endoscopic image analysis, Second IASTED International Conference on Biomedical Engineering, Innsbruck, Austria, 405–408 (2004)

    Google Scholar 

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

    Google Scholar 

  14. Kodogiannis V.S., Boulougoura M., Wadge E., Lygouras J.N.: The usage of soft-computing methodologies in interpreting capsule endoscopy, Engineering Applications in Artificial Intelligence, Elsevier, 20 539–553 (2007)

    Article  Google Scholar 

  15. Kuncheva, L.I.: Fuzzy Classifier Design, Physica, Heidelberg (2000)

    MATH  Google Scholar 

  16. Wadge, E.: The use of EM-Based neural network schemes for modelling and classification, PhD Thesis, Westminster University, (2005)

    Google Scholar 

  17. Arena, A., Boulougoura, M., Chowdrey, H.S., Dario, P., Harendt, C., Irion, K.-M., Kodogiannis, V., Lenaerts, B., Menciassi, A., Puers, R., Scherjon, C., Turgis, D.: Intracorporeal Videoprobe (IVP), in Medical and Care Computing 2, Volume 114 Studies in Health Technology and Informatics, Edited by: Bos, L. Laxminarayan, S. and Marsh, A. IOS Press, Amsterdam, Netherlands, 167–174 (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Kodogiannis, V.S., Lygouras, J.N., Pachidis, T. (2008). An Intelligent Decision Support System in Wireless-Capsule Endoscopy. In: Chountas, P., Petrounias, I., Kacprzyk, J. (eds) Intelligent Techniques and Tools for Novel System Architectures. Studies in Computational Intelligence, vol 109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77623-9_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-77623-9_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77621-5

  • Online ISBN: 978-3-540-77623-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics