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Fuzzy Relational Pattern Dynamics of the Breast Cancer Cells

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Soft Computing and Industry

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Abstract

In this study, the microcalcification modeling problem has been handled to detect the microcalcification clusters. The detection of microcalcifications is carried out over the filtered mammogram image. It is observed that, the histograms of the band-pass filtered subimages are very close to the Gaussian distribution.

Our detection schemes are modeled by fuzzy relational matrix estimating microcalcifications automatically in each square region. If a region has high positive skewness and kurtosis then it is marked as a region of interest. Both the skewness and the kurtosis assume very small values in the healty breast region, while they have high values in the region containing microcalcifications. Experimental results confirm our detection scheme.

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Author information

Authors and Affiliations

  1. Dept. of Chemical Engineering, Ankara University, Engineering Faculty, Turkey

    Z. Zeybek

  2. Dept. of Electronics Engineering, Ankara University, Engineering Faculty, Turkey

    Z. Telatar & Y. Öztürk

Authors
  1. Z. Zeybek
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  2. Z. Telatar
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  3. Y. Öztürk
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Editor information

Editors and Affiliations

  1. Enterprise Integration, Cranfield University, Cranfield, Bedford, MK43 0AL, UK

    Rajkumar Roy PhD

  2. Department of Pattern Recognition, Fraunhofer IPK-Berlin, Pascalstrasse 8-9, Berlin, 10587, Germany

    Mario Köppen Diplom-Phys

  3. Institute of Intelligent Electronics, Helsinki University of Technology, Otakaari 5 A, FIN-02150, Espoo, Finland

    Seppo Ovaska PhD

  4. Department of Information Engineering, Mie University, 1515 Kamihama-cho, Tsu, 514-8507, Japan

    Takeshi Furuhashi PhD

  5. Royal Institute of Technology, NADA/CV AP, 10044, Stockholm, Sweden

    Frank Hoffmann

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© 2002 Springer-Verlag London

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Zeybek, Z., Telatar, Z., Öztürk, Y. (2002). Fuzzy Relational Pattern Dynamics of the Breast Cancer Cells. In: Roy, R., Köppen, M., Ovaska, S., Furuhashi, T., Hoffmann, F. (eds) Soft Computing and Industry. Springer, London. https://doi.org/10.1007/978-1-4471-0123-9_32

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  • DOI: https://doi.org/10.1007/978-1-4471-0123-9_32

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-1101-6

  • Online ISBN: 978-1-4471-0123-9

  • eBook Packages: Springer Book Archive

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