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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 114–121Cite as

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A Novel Approach for Global Lung Registration Using 3D Markov-Gibbs Appearance Model

A Novel Approach for Global Lung Registration Using 3D Markov-Gibbs Appearance Model

  • Ayman El-Baz19,
  • Fahmi Khalifa19,
  • Ahmed Elnakib19,
  • Matthew Nitzken19,
  • Ahmed Soliman19,
  • Patrick McClure19,
  • Mohamed Abou El-Ghar20 &
  • …
  • Georgy Gimel’farb21 
  • Conference paper
  • 3990 Accesses

  • 6 Citations

Part of the Lecture Notes in Computer Science book series (LNIP,volume 7511)

Abstract

A new approach to align 3D CT data of a segmented lung object with a given prototype (reference lung object) using an affine transformation is proposed. Visual appearance of the lung from CT images, after equalizing their signals, is modeled with a new 3D Markov-Gibbs random field (MGRF) with pairwise interaction model. Similarity to the prototype is measured by a Gibbs energy of signal co-occurrences in a characteristic subset of voxel pairs derived automatically from the prototype. An object is aligned by an affine transformation maximizing the similarity by using an automatic initialization followed by a gradient search. Experiments confirm that our approach aligns complex objects better than popular conventional algorithms.

Keywords

  • Gibbs Energy
  • Mutual Information
  • Image Registration
  • Characteristic Subset
  • Appearance Model

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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Author information

Authors and Affiliations

  1. BioImaging Laboratory, Bioengineering Department, University of Louisville, Louisville, KY, USA

    Ayman El-Baz, Fahmi Khalifa, Ahmed Elnakib, Matthew Nitzken, Ahmed Soliman & Patrick McClure

  2. Radiology Department, Urology and Nephrology Center, University of Mansoura, Mansoura, 35516, Egypt

    Mohamed Abou El-Ghar

  3. Department of Computer Science, University of Auckland, Auckland, New Zealand

    Georgy Gimel’farb

Authors
  1. Ayman El-Baz
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  2. Fahmi Khalifa
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  3. Ahmed Elnakib
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  4. Matthew Nitzken
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  5. Ahmed Soliman
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  6. Patrick McClure
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  7. Mohamed Abou El-Ghar
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  8. Georgy Gimel’farb
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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

El-Baz, A. et al. (2012). A Novel Approach for Global Lung Registration Using 3D Markov-Gibbs Appearance Model. 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 7511. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33418-4_15

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  • DOI: https://doi.org/10.1007/978-3-642-33418-4_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33417-7

  • Online ISBN: 978-3-642-33418-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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