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TomoGC: Binary Tomography by Constrained GraphCuts

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Pattern Recognition (DAGM 2015)

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Abstract

We present an iterative reconstruction algorithm for binary tomography, called TomoGC, that solves the reconstruction problem based on a constrained graphical model by a sequence of graphcuts. TomoGC reconstructs objects even if a low number of measurements are only given, which enables shorter observation periods and lower radiation doses in industrial and medical applications. We additionally suggest some modifications of established methods that improve state-of-the-art methods. A comprehensive numerical evaluation demonstrates that the proposed method can reconstruct objects from a small number of projections more accurate and also faster than competitive methods.

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  1. 1.

    http://www.cs.ubc.ca/~schmidtm/Software/minConf.html.

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Acknowledgements

Financial support of our research work by the DFG, grant GRK 1653. is gratefully acknowledged.

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Authors and Affiliations

  1. Heidelberg University, Heidelberg, Germany

    Jörg Hendrik Kappes, Stefania Petra, Christoph Schnörr & Matthias Zisler

Authors
  1. Jörg Hendrik Kappes
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  2. Stefania Petra
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  3. Christoph Schnörr
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  4. Matthias Zisler
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Correspondence to Jörg Hendrik Kappes .

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Editors and Affiliations

  1. Institute of Computer Science III, University of Bonn, Bonn, Germany

    Juergen Gall

  2. MPI for Intelligent Systems, University of Tübingen, Tübingen, Germany

    Peter Gehler

  3. Computer Vision Group, Visual Computing Institute, RWTH Aachen, Aachen, Germany

    Bastian Leibe

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Kappes, J.H., Petra, S., Schnörr, C., Zisler, M. (2015). TomoGC: Binary Tomography by Constrained GraphCuts. In: Gall, J., Gehler, P., Leibe, B. (eds) Pattern Recognition. DAGM 2015. Lecture Notes in Computer Science(), vol 9358. Springer, Cham. https://doi.org/10.1007/978-3-319-24947-6_21

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  • DOI: https://doi.org/10.1007/978-3-319-24947-6_21

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  • Online ISBN: 978-3-319-24947-6

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