title: Entropy-based particle correspondence for shape populations.
abstract: OBJECTIVE
  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.
authors.affiliation: University of Iowa, Iowa City, IA, USA. ipek-oguz@uiowa.edu.
authors.forename: Ipek
authors.initials: I
authors.lastname: Oguz
authors.affiliation: University of Utah, Salt Lake City, UT, USA.
authors.forename: Josh
authors.initials: J
authors.lastname: Cates
authors.affiliation: University of Utah, Salt Lake City, UT, USA.
authors.forename: Manasi
authors.initials: M
authors.lastname: Datar
authors.affiliation: University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
authors.forename: Beatriz
authors.initials: B
authors.lastname: Paniagua
authors.affiliation: University of Utah, Salt Lake City, UT, USA.
authors.forename: Thomas
authors.initials: T
authors.lastname: Fletcher
authors.affiliation: University of Utah, Salt Lake City, UT, USA.
authors.forename: Clement
authors.initials: C
authors.lastname: Vachet
authors.affiliation: University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
authors.forename: Martin
authors.initials: M
authors.lastname: Styner
authors.affiliation: University of Utah, Salt Lake City, UT, USA.
authors.forename: Ross
authors.initials: R
authors.lastname: Whitaker
mesh_terms: D000465:Algorithms; D019277:Entropy; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Correspondence; Entropy; Shape analysis