Entropy-based particle correspondence for shape populations

  • Ipek Oguz
  • Josh Cates
  • Manasi Datar
  • Beatriz Paniagua
  • Thomas Fletcher
  • Clement Vachet
  • Martin Styner
  • Ross Whitaker
Review Article

DOI: 10.1007/s11548-015-1319-6

Cite this article as:
Oguz, I., Cates, J., Datar, M. et al. Int J CARS (2016) 11: 1221. doi:10.1007/s11548-015-1319-6
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Abstract

Purpose

Statistical shape analysis of anatomical structures plays an important role in many medical image analysis applications such as understanding the structural changes in anatomy in various stages of growth or disease. Establishing accurate correspondence across object populations is essential for such statistical shape analysis studies.

Methods

In this paper, we present an entropy-based correspondence framework for computing point-based correspondence among populations of surfaces in a groupwise manner. This robust framework is parameterization-free and computationally efficient. We review the core principles of this method as well as various extensions to deal effectively with surfaces of complex geometry and application-driven correspondence metrics.

Results

We apply our method to synthetic and biological datasets to illustrate the concepts proposed and compare the performance of our framework to existing techniques.

Conclusions

Through the numerous extensions and variations presented here, we create a very flexible framework that can effectively handle objects of various topologies, multi-object complexes, open surfaces, and objects of complex geometry such as high-curvature regions or extremely thin features.

Keywords

Correspondence Shape analysis Entropy 

Copyright information

© CARS 2015

Authors and Affiliations

  • Ipek Oguz
    • 1
  • Josh Cates
    • 2
  • Manasi Datar
    • 2
  • Beatriz Paniagua
    • 3
  • Thomas Fletcher
    • 2
  • Clement Vachet
    • 2
  • Martin Styner
    • 3
  • Ross Whitaker
    • 2
  1. 1.University of IowaIowa CityUSA
  2. 2.University of UtahSalt Lake CityUSA
  3. 3.University of North Carolina at Chapel HillChapel HillUSA