Comparing the similarity of statistical shape models using the bhattacharya metric

K. O. Babalola, T. F. Cootes, B. Patenaude, A. Rao, M. Jenkinson

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

8 Citations (Scopus)

Abstract

A variety of different methods of finding correspondences across sets of images to build statistical shape models have been proposed, each of which is likely to result in a different model. When dealing with large datasets (particularly in 3D), it is difficult to evaluate the quality of the resulting models. However, if the different methods are successfully modelling the true underlying shape variation, the resulting models should be similar. If two different techniques lead to similar models, it suggests that they are indeed approximating the true shape change. In this paper we explore a method of comparing statistical shape models by evaluating the Bhattacharya overlap between their implied shape distributions. We apply the technique to investigate the similarity of three models of the same 3D dataset constructed using different methods.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - 9th International Conference, Proceedings
PublisherSpringer Verlag
Pages142-150
Number of pages9
ISBN (Print)3540447075, 9783540447078
DOIs
Publication statusPublished or Issued - 2006
Externally publishedYes
Event9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - Copenhagen, Denmark
Duration: 1 Oct 20066 Oct 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4190 LNCS - I
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006
Country/TerritoryDenmark
CityCopenhagen
Period1/10/066/10/06

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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