Geodesic Distances to Landmarks for Dense Correspondence on Ensembles of Complex Shapes

  • Manasi Datar
  • Ilwoo Lyu
  • SunHyung Kim
  • Joshua Cates
  • Martin A. Styner
  • Ross Whitaker
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8150)


Establishing correspondence points across a set of biomedical shapes is an important technology for a variety of applications that rely on statistical analysis of individual subjects and populations. The inherent complexity (e.g. cortical surface shapes) and variability (e.g. cardiac chambers) evident in many biomedical shapes introduce significant challenges in finding a useful set of dense correspondences. Application specific strategies, such as registration of simplified (e.g. inflated or smoothed) surfaces or relying on manually placed landmarks, provide some improvement but suffer from limitations including increased computational complexity and ambiguity in landmark placement. This paper proposes a method for dense point correspondence on shape ensembles using geodesic distances to a priori landmarks as features. A novel set of numerical techniques for fast computation of geodesic distances to point sets is used to extract these features. The proposed method minimizes the ensemble entropy based on these features, resulting in isometry invariant correspondences in a very general, flexible framework.


Left Atrium Geodesic Distance Cortical Surface Eikonal Equation Automatic Correspondence 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Manasi Datar
    • 1
  • Ilwoo Lyu
    • 2
  • SunHyung Kim
    • 3
  • Joshua Cates
    • 1
    • 4
  • Martin A. Styner
    • 2
    • 3
  • Ross Whitaker
    • 1
  1. 1.Scientific Computing and Imaging InstituteUniversity of UtahUSA
  2. 2.Department of Computer ScienceUniversity of North Carolina at Chapel HillUSA
  3. 3.Department of PsychiatryUniversity of North Carolina at Chapel HillUSA
  4. 4.CARMA CenterUniversity of UtahUSA

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