Topology preserving brain tissue segmentation using graph cuts

Xinyang Liu, Pierre Louis Bazin, Aaron Carass, Jerry Prince

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

Abstract

In segmentation of magnetic resonance brain images, it is important to maintain topology of the segmented structures. In this work, we present a framework to segment multiple objects in a brain image while preserving the topology of each object as given in an initial topological template. The framework combines the advantages of digital topology and several existing techniques in graph cuts segmentation. The proposed technique can handle any given topology and enforces object-level relationships with little constraint over the geometry. We apply our algorithm to brain tissue segmentation and demonstrate its accuracy and computational efficiency.

Original languageEnglish (US)
Title of host publication2012 IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, MMBIA 2012
Pages185-190
Number of pages6
DOIs
StatePublished - 2012
Event2012 IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, MMBIA 2012 - Breckenridge, CO, United States
Duration: Jan 9 2012Jan 10 2012

Publication series

NameProceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis

Other

Other2012 IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, MMBIA 2012
Country/TerritoryUnited States
CityBreckenridge, CO
Period1/9/121/10/12

ASJC Scopus subject areas

  • Applied Mathematics
  • Radiology Nuclear Medicine and imaging
  • Biomedical Engineering

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