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International Conference on Medical Image Computing and Computer-Assisted Intervention

MICCAI 2012: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012 pp 115–122Cite as

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Globally Optimal Deformable Registration on a Minimum Spanning Tree Using Dense Displacement Sampling

Globally Optimal Deformable Registration on a Minimum Spanning Tree Using Dense Displacement Sampling

  • Mattias P. Heinrich19,20,
  • Mark Jenkinson20,
  • Sir Michael Brady21 &
  • …
  • Julia A. Schnabel19 
  • Conference paper
  • 4643 Accesses

  • 21 Citations

Part of the Lecture Notes in Computer Science book series (LNIP,volume 7512)

Abstract

Deformable image registration poses a highly non-convex optimisation problem. Conventionally, medical image registration techniques rely on continuous optimisation, which is prone to local minima. Recent advances in the mathematics and new programming methods enable these disadvantages to be overcome using discrete optimisation. In this paper, we present a new technique deeds, which employs a discrete dense displacement sampling for the deformable registration of high resolution CT volumes. The image grid is represented as a minimum spanning tree. Given these constraints a global optimum of the cost function can be found efficiently using dynamic programming, which enforces the smoothness of the deformations. Experimental results demonstrate the advantages of deeds: the registration error for the challenging registration of inhale and exhale pulmonary CT scans is significantly lower than for two state-of-the-art registration techniques, especially in the presence of large deformations and sliding motion at lung surfaces.

Keywords

  • Image Registration
  • Minimum Span Tree
  • Markov Random Field
  • Discrete Optimisation
  • Registration Error

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Author information

Authors and Affiliations

  1. Institute of Biomedical Engineering, University of Oxford, UK

    Mattias P. Heinrich & Julia A. Schnabel

  2. Oxford University Centre for Functional MRI of the Brain, UK

    Mattias P. Heinrich & Mark Jenkinson

  3. Department of Oncology, University of Oxford, UK

    Sir Michael Brady

Authors
  1. Mattias P. Heinrich
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  2. Mark Jenkinson
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  3. Sir Michael Brady
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  4. Julia A. Schnabel
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Editor information

Editors and Affiliations

  1. Project Team Asclepios, Inria Sophia Antipolis, 06902, Sophia-Antipolis, France

    Nicholas Ayache & Hervé Delingette & 

  2. MIT, CSAIL, 02139, Cambridge, MA, USA

    Polina Golland

  3. Information and Communication Headquarters, Nagoya University, 464-8603, Nagoya, Japan

    Kensaku Mori

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© 2012 Springer-Verlag Berlin Heidelberg

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Heinrich, M.P., Jenkinson, M., Brady, S.M., Schnabel, J.A. (2012). Globally Optimal Deformable Registration on a Minimum Spanning Tree Using Dense Displacement Sampling. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012. MICCAI 2012. Lecture Notes in Computer Science, vol 7512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33454-2_15

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  • DOI: https://doi.org/10.1007/978-3-642-33454-2_15

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  • Print ISBN: 978-3-642-33453-5

  • Online ISBN: 978-3-642-33454-2

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