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Application of Wavelet Transforms and Bayes Classifier to Segmentation of Ultrasound Images

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Pattern Recognition and Image Analysis (IbPRIA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3523))

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Abstract

An approach for segmentation of ultrasound images using features extracted by orthogonal wavelet transforms that can be used in an interactive system is proposed. These features are the training data for the K-means clustering algorithm and the Bayes classifier. The result of classification is improved by using neighbourhood information.

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Author information

Authors and Affiliations

  1. Institute of Fundamental Technological Research, Polish Academy of Sciences, 21 Swietokrzyska Str, 00-049, Warsaw, Poland

    Paweł Kieś

Authors
  1. Paweł Kieś
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Editor information

Editors and Affiliations

  1. Instituto Superior Técnico & Instituto de Sistemas e Robótica,, 1049-001, Lisboa, Portugal

    Jorge S. Marques

  2. ETSI Informática y e Telecomunicación, University of Granada, 18071, Granada, Spain

    Nicolás Pérez de la Blanca

  3. Instituto Superior Técnico, CERENA-Centro de Recursos Naturais e Ambiente, Av. Rovisco Pais, 1049-001, Lisboa, Portugal

    Pedro Pina

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© 2005 Springer-Verlag Berlin Heidelberg

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Kieś, P. (2005). Application of Wavelet Transforms and Bayes Classifier to Segmentation of Ultrasound Images. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11492542_42

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  • DOI: https://doi.org/10.1007/11492542_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26154-4

  • Online ISBN: 978-3-540-32238-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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