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Active Region Approach for Segmentation of Medical Images

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Artificial Intelligence and Soft Computing (ICAISC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8468))

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Abstract

Active region models are methods for automatic image segmentation. In this paper, the method is examined using various medical images (heart, brain and liver). The quality measure, taken for evaluation of the method is based on combination of two measures used for classifiers. The energy of the region is based on statistical features of initial region.

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Author information

Authors and Affiliations

  1. Institute of Information Technology, Lodz University of Technology, ul. Wolczanska 215, 90-924, Poland

    Pawel Tracz & Piotr S. Szczepaniak

Authors
  1. Pawel Tracz
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  2. Piotr S. Szczepaniak
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Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Armii Krajowej 36, 42-200, Częstochowa, Poland

    Leszek Rutkowski  & Rafał Scherer  & 

  2. Częstochowa University of Technology, 42-200, Częstochowa, Poland

    Marcin Korytkowski

  3. AGH University of Science and Technology, Mickiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Computer Science Division, Department of Electrical Engineering and Computer Sciences, University of California Berkeley, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  5. Computational Intelligence Laboratory, Electrical and Computer Engineering, University of Louisville, 405 Lutz Hall, 40292, Louisville, KY, USA

    Jacek M. Zurada

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© 2014 Springer International Publishing Switzerland

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Tracz, P., Szczepaniak, P.S. (2014). Active Region Approach for Segmentation of Medical Images. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2014. Lecture Notes in Computer Science(), vol 8468. Springer, Cham. https://doi.org/10.1007/978-3-319-07176-3_18

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  • DOI: https://doi.org/10.1007/978-3-319-07176-3_18

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07175-6

  • Online ISBN: 978-3-319-07176-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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