Statistical shape analysis for population studies via level-set based shape morphing

Tammy Riklin Raviv, Yi Gao, James J. Levitt, Sylvain Bouix

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


We present a method that allows the detection, localization and quantification of statistically significant morphological differences in complex brain structures between populations. This is accomplished by a novel level-set framework for shape morphing and a multi-shape dissimilarity-measure derived by a modified version of the Hausdorff distance. The proposed method does not require explicit one-to-one point correspondences and is fast, robust and easy to implement regardless of the topological complexity of the anatomical surface under study. The proposed model has been applied to different populations using a variety of brain structures including left and right striatum, caudate, amygdala-hippocampal complex and superior- temporal gyrus (STG) in normal controls and patients. The synthetic databases allow quantitative evaluations of the proposed algorithm while the results obtained for the real clinical data are in line with published findings on gray matter reduction in the tested cortical and sub-cortical structures in schizophrenia patients.

Original languageEnglish
Title of host publicationComputer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings
PublisherSpringer Verlag
Number of pages10
EditionPART 1
ISBN (Print)9783642338625
StatePublished - 1 Jan 2012
Externally publishedYes
Event12th European Conference on Computer Vision, ECCV 2012 - Florence, Italy
Duration: 7 Oct 201213 Oct 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume7583 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference12th European Conference on Computer Vision, ECCV 2012

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)


Dive into the research topics of 'Statistical shape analysis for population studies via level-set based shape morphing'. Together they form a unique fingerprint.

Cite this