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Network Flow Algorithms for Discrete Tomography

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Advances in Discrete Tomography and Its Applications

Part of the book series: Applied and Numerical Harmonic Analysis ((ANHA))

Abstract

There exists an elegant correspondence between the problem of reconstructing a 0-1 lattice image from two of its projections and the problem of finding a maximum flow in a certain graph. In this chapter we describe how network flow algorithms can be used to solve a variety of problems from discrete tomography. First, we describe the network flow approach for two projections and several of its generalizations. Subsequently, we present an algorithm for reconstructing 0-1 images from more than two projections. The approach is extended to the reconstruction of 3D images and images that do not have an intrinsic lattice structure.

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Author information

Authors and Affiliations

  1. CWI, Amsterdam and Mathematical Institute, Leiden University, P.O. Box9512, 2300 RA Leiden, The Netherlands

    K.J. Batenburg

Authors
  1. K.J. Batenburg
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Editor information

Editors and Affiliations

  1. Program in Computer Science The Graduate Center, The City University of New York, 365 Fifth Avenue, New York, NY, 10016, USA

    Gabor T. Herman

  2. Department of Image Processing and Computer Graphics, University of Szeged, Árpád tér 2 H-6720 , Szeged, Hungary

    Attila Kuba

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© 2007 Birkhäuser Boston

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Batenburg, K. (2007). Network Flow Algorithms for Discrete Tomography. In: Herman, G.T., Kuba, A. (eds) Advances in Discrete Tomography and Its Applications. Applied and Numerical Harmonic Analysis. Birkhäuser Boston. https://doi.org/10.1007/978-0-8176-4543-4_9

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  • DOI: https://doi.org/10.1007/978-0-8176-4543-4_9

  • Publisher Name: Birkhäuser Boston

  • Print ISBN: 978-0-8176-3614-2

  • Online ISBN: 978-0-8176-4543-4

  • eBook Packages: EngineeringEngineering (R0)

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