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Computational Intelligence Techniques in Image Segmentation for Cytopathology

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Computational Intelligence in Biomedicine and Bioinformatics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 151))

Summary

A variety of computational intelligence approaches to nuclei segmentation in the microscope images of fine needle biopsy material is presented in this chapter. The segmentation is one of the most important steps of the automatic medical diagnosis based on the analysis of the microscopic images, and is crucial to making a correct diagnostic decision. Due to complex nature of biological images, standard segmentation methods are not effective enough. In this chapter we present and discuss some modified versions of watershed algorithm, active contours, cellular automata, GrowCut technique, as well as new approaches like fuzzy sets of I and II type, and the sonar-like method.

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Authors and Affiliations

  1. Institute of Control and Computation Engineering, University of Zielona Góra, ul. Podgórna 50, 65-246, Zielona Góra, Poland

    Andrzej Obuchowicz, Maciej Hrebień, Tomasz Nieczkowski & Andrzej Marciniak

Authors
  1. Andrzej Obuchowicz
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  2. Maciej Hrebień
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  3. Tomasz Nieczkowski
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  4. Andrzej Marciniak
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Editors and Affiliations

  1. Department of Biology, Emory University, 1510 Clifton Rd.NE, 30322, Atlanta, Georgia, USA

    Tomasz G. Smolinski

  2. Department of Computer Science, University of Arkansas at Little Rock, 2801 S.University Ave., 72204, Little Rock, Arkansas, USA

    Mariofanna G. Milanova

  3. Department of Quantitative Methods and Information Systems College of Business and Administration, Kuwait University, P.O. Box 5486, 13055, Safat, Kuwait

    Aboul-Ella Hassanien

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Obuchowicz, A., Hrebień, M., Nieczkowski, T., Marciniak, A. (2008). Computational Intelligence Techniques in Image Segmentation for Cytopathology. In: Smolinski, T.G., Milanova, M.G., Hassanien, AE. (eds) Computational Intelligence in Biomedicine and Bioinformatics. Studies in Computational Intelligence, vol 151. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70778-3_7

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  • DOI: https://doi.org/10.1007/978-3-540-70778-3_7

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