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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 131–138Cite as

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Regional Manifold Learning for Deformable Registration of Brain MR Images

Regional Manifold Learning for Deformable Registration of Brain MR Images

  • Dong Hye Ye19,
  • Jihun Hamm20,
  • Dongjin Kwon19,
  • Christos Davatzikos19 &
  • …
  • Kilian M. Pohl19 
  • Conference paper
  • 4309 Accesses

  • 10 Citations

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

Abstract

We propose a method for deformable registration based on learning the manifolds of individual brain regions. Recent publications on registration of medical images advocate the use of manifold learning in order to confine the search space to anatomically plausible deformations. Existing methods construct manifolds based on a single metric over the entire image domain thus frequently miss regional brain variations. We address this issue by first learning manifolds for specific regions and then computing region-specific deformations from these manifolds. We then determine deformations for the entire image domain by learning the global manifold in such a way that it preserves the region-specific deformations. We evaluate the accuracy of our method by applying it to the LPBA40 dataset and measuring the overlap of the deformed segmentations. The result shows significant improvement in registration accuracy on cortex regions compared to other state of the art methods.

Keywords

  • Manifold Learning
  • Image Registration
  • Brain MRI

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Author information

Authors and Affiliations

  1. Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA, 19104

    Dong Hye Ye, Dongjin Kwon, Christos Davatzikos & Kilian M. Pohl

  2. Department of Computer Science, Ohio State University, Columbus, OH, 43210, USA

    Jihun Hamm

Authors
  1. Dong Hye Ye
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  2. Jihun Hamm
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  3. Dongjin Kwon
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  4. Christos Davatzikos
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  5. Kilian M. Pohl
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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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Cite this paper

Ye, D.H., Hamm, J., Kwon, D., Davatzikos, C., Pohl, K.M. (2012). Regional Manifold Learning for Deformable Registration of Brain MR Images. 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_17

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  • DOI: https://doi.org/10.1007/978-3-642-33454-2_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33453-5

  • Online ISBN: 978-3-642-33454-2

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