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Cardiac Ventricle Contour Reconstruction in Ultrasonographic Images Using Bayesian Constrained Spectral Method

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Artificial Intelligence and Soft Computing – ICAISC 2006 (ICAISC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4029))

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Abstract

We propose a novel method of active spectral segmentation of cardiac ventricle by application of Bayesian inference adapted to contour detection in speckled ultrasonographic cardiological data. We discuss the advantages and limitations of this method and describe possible further developments.

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Authors and Affiliations

  1. Institute of Precision and Biomedical Engineering, Department of Mechatronics, Warsaw University of Technology, Św. Andrzeja Boboli 8, 02-525, Warsaw, Poland

    Tomasz Sołtysiński, Krzysztof Kałużynski & Tadeusz Pałko

Authors
  1. Tomasz Sołtysiński
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  2. Krzysztof Kałużynski
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  3. Tadeusz Pałko
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Department of Electrical Engineering and Computer Sciences, Berkeley Initiative in Soft Computing (BISC), University of California, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  4. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Żurada

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© 2006 Springer-Verlag Berlin Heidelberg

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Sołtysiński, T., Kałużynski, K., Pałko, T. (2006). Cardiac Ventricle Contour Reconstruction in Ultrasonographic Images Using Bayesian Constrained Spectral Method. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science(), vol 4029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11785231_104

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  • DOI: https://doi.org/10.1007/11785231_104

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35748-3

  • Online ISBN: 978-3-540-35750-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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