Toads: Topology-preserving, anatomy-driven segmentation

Pierre Louis Bazin, Dzung L. Pham

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a new algorithm for object segmentation in medical images that respects the topological properties and anatomical relationships of structures as given by a template. The technique combines advantages of tissue classification, digital topology, and image registration to handle any given topology and enforces object-level relationships with little constraint over the geometry. It is applied to cortical segmentation and validated on simulated and real images.

Original languageEnglish (US)
Title of host publication2006 3rd IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro - Proceedings
Pages327-330
Number of pages4
StatePublished - Nov 17 2006
Event2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Arlington, VA, United States
Duration: Apr 6 2006Apr 9 2006

Publication series

Name2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings
Volume2006

Other

Other2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro
CountryUnited States
CityArlington, VA
Period4/6/064/9/06

ASJC Scopus subject areas

  • Engineering(all)

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