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Geometric-Feature-Based Spectral Graph Matching in Pharyngeal Surface Registration

  • Qingyu Zhao
  • Stephen Pizer
  • Marc Niethammer
  • Julian Rosenman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8673)

Abstract

Fusion between an endoscopic movie and a CT can aid specifying the tumor target volume for radiotherapy. That requires a deformable pharyngeal surface registration between a 3D endoscope reconstruction and a CT segmentation. In this paper, we propose to use local geometric features for deriving a set of initial correspondences between two surfaces, with which an association graph can be constructed for registration by spectral graph matching. We also define a new similarity measurement to provide a meaningful way for computing inter-surface affinities in the association graph. Our registration method can deal with large non-rigid anatomical deformation, as well as missing data and topology change. We tested the robustness of our method with synthetic deformations and showed registration results on real data.

Keywords

Partial Surface Registration Error Initial Link Spectral Graph Surface Registration 
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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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Qingyu Zhao
    • 1
  • Stephen Pizer
    • 1
  • Marc Niethammer
    • 1
  • Julian Rosenman
    • 2
  1. 1.Computer ScienceUNC Chapel HillUnited States
  2. 2.Radiation OncologyUNC Chapel HillUnited States

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