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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 147–155Cite as

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  2. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012
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A Hierarchical Scheme for Geodesic Anatomical Labeling of Airway Trees

A Hierarchical Scheme for Geodesic Anatomical Labeling of Airway Trees

  • Aasa Feragen19,
  • Jens Petersen19,
  • Megan Owen20,
  • Pechin Lo19,21,
  • Laura H. Thomsen22,
  • Mathilde M. W. Wille22,
  • Asger Dirksen22 &
  • …
  • Marleen de Bruijne19,23 
  • Conference paper
  • 4345 Accesses

  • 12 Citations

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

Abstract

We present a fast and robust supervised algorithm for labeling anatomical airway trees, based on geodesic distances in a geometric tree-space. Possible branch label configurations for a given tree are evaluated based on distances to a training set of labeled trees. In tree-space, the tree topology and geometry change continuously, giving a natural way to automatically handle anatomical differences and noise. The algorithm is made efficient using a hierarchical approach, in which labels are assigned from the top down. We only use features of the airway centerline tree, which are relatively unaffected by pathology.

A thorough leave-one-patient-out evaluation of the algorithm is made on 40 segmented airway trees from 20 subjects labeled by 2 medical experts. We evaluate accuracy, reproducibility and robustness in patients with Chronic Obstructive Pulmonary Disease (COPD). Performance is statistically similar to the inter- and intra-expert agreement, and we found no significant correlation between COPD stage and labeling accuracy.

Keywords

  • airway tree labeling
  • geodesic matching

image.diku.dk/aasa/miccai_supplemental.tar.gz

Description: This is a zipped folder which contains a complete list of our labeling results, plots of the labeled airway trees, and plots of the combinatorial structures of the airway trees, to give the reader insight into the problem.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Copenhagen, Denmark

    Aasa Feragen, Jens Petersen, Pechin Lo & Marleen de Bruijne

  2. David R. Cheriton School of Computer Science, University of Waterloo, Canada

    Megan Owen

  3. Department of Radiology, University of California, Los Angeles, USA

    Pechin Lo

  4. Lungemedicinsk afdeling, Gentofte Hospital, Denmark

    Laura H. Thomsen, Mathilde M. W. Wille & Asger Dirksen

  5. Biomedical Imaging Group Rotterdam, Erasmus MC, The Netherlands

    Marleen de Bruijne

Authors
  1. Aasa Feragen
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  2. Jens Petersen
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  3. Megan Owen
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  4. Pechin Lo
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  5. Laura H. Thomsen
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  6. Mathilde M. W. Wille
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  7. Asger Dirksen
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  8. Marleen de Bruijne
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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

Feragen, A. et al. (2012). A Hierarchical Scheme for Geodesic Anatomical Labeling of Airway Trees. 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_19

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  • DOI: https://doi.org/10.1007/978-3-642-33454-2_19

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  • Print ISBN: 978-3-642-33453-5

  • Online ISBN: 978-3-642-33454-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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