Statistical and topological atlas based brain image segmentation

Pierre Louis Bazin*, Dzung L. Pham

*Corresponding author for this work

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

18 Scopus citations

Abstract

This paper presents a new atlas-based segmentation framework for the delineation of major regions in magnetic resonance brain images employing an atlas of the global topological structure as well as a statistical atlas of the regions of interest. A segmentation technique using fast marching methods and tissue classification is proposed that guarantees strict topological equivalence between the segmented image and the atlas. Experimental validation on simulated and real brain images shows that the method is accurate and robust.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - 10th International Conference, Proceedings
PublisherSpringer Verlag
Pages94-101
Number of pages8
EditionPART 1
ISBN (Print)9783540757566
DOIs
StatePublished - 2007
Event10th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2007 - Brisbane, Australia
Duration: 29 Oct 20072 Nov 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4791 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2007
Country/TerritoryAustralia
CityBrisbane
Period29/10/072/11/07

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