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A Three-Dimentional Neural Network Based Approach to the Image Reconstruction from Projections Problem

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Artificial Intelligence and Soft Computing (ICAISC 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6113))

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Abstract

This paper presents a novel neural network approach to the problem of image reconstruction from projections obtained by spiral tomography scanner. The reconstruction process is performed during the minimizing of the energy function in recurrent neural network. Our method is of a great practical use in reconstruction from discrete cone-beam projections. Experimental results show that the appropriately designed neural network is able to reconstruct an image with better quality than obtained from used commercial conventional algorithms.

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Author information

Authors and Affiliations

  1. Departament of Computer Engineering, Technical University of Czestochowa, Armii Krajowej 36, 42-200, Czestochowa, Poland

    Robert Cierniak

Authors
  1. Robert Cierniak
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Editor information

Editors and Affiliations

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

    Leszek Rutkowski

  2. Academy of Humanities and Economics in Łódź,, ul. Rewolucji 1905 nr 64, Łódź, Poland

    Rafał Scherer

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

    Ryszard Tadeusiewicz

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

    Lotfi A. Zadeh

  5. Computational Intelligence Laboratory Department of Electrical and Computer Engineering, University of Louisville, 40292, Louisville, KY

    Jacek M. Zurada

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© 2010 Springer-Verlag Berlin Heidelberg

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Cierniak, R. (2010). A Three-Dimentional Neural Network Based Approach to the Image Reconstruction from Projections Problem. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2010. Lecture Notes in Computer Science(), vol 6113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13208-7_63

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  • DOI: https://doi.org/10.1007/978-3-642-13208-7_63

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13207-0

  • Online ISBN: 978-3-642-13208-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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