Topology preserving tissue classification with fast marching and topology templates

Pierre Louis Bazin, Dzung L. Pham

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper presents a novel approach for object segmentation in medical images that respects the topological relationships of multiple structures as given by a template. The algorithm combines advantages of tissue classification, digital topology, and level-set evolution into a topology-invariant multiple-object fast marching method. The technique can handle any given topology and enforces object-level relationships with little constraint over the geometry. Applied to brain segmentation, it sucessfully extracts gray matter and white matter structures with the correct spherical topology without topology correction or editing of the subcortical structures.

Original languageEnglish (US)
Pages (from-to)234-245
Number of pages12
JournalLecture Notes in Computer Science
Volume3565
StatePublished - Oct 17 2005
Event19th International Conference on Information Processing in Medical Imaging, IPMI 2005 - Glenwood Springs, CO, United States
Duration: Jul 10 2005Jul 15 2005

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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