A deformable cosegmentation algorithm for brain MR images

Tong Zhang, Yong Xia, David Dagan Feng

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

11 Scopus citations

Abstract

Cosegmentation aims to simultaneously segment the common parts in a pair of images, and has recently attracted increasing research attention in the field of computer vision. In this paper, we propose a novel deformable cosegmentation (D-C) algorithm to solve the brain MR image segmentation problem by cosegmenting the image and a co-registered atlas. In this manner, the prior heuristic information about brain anatomy that is embedded in the atlas can be transformed into the constraints that control the segmentation of brain MR images. Based on the multiphase Chan-Vese model, the proposed D-C algorithm is implemented using level set techniques. Then, it is compared to the protocol algorithm and the state-of-the-art GA-EM algorithm in T1-weighted brain MR images corrupted by different levels of Gaussian noise and intensity non-uniformity. Our results show that the proposed D-C algorithm can differentiate major brain structures more accuratly and produce more robust segmentation of brain MR images.

Original languageEnglish
Title of host publication2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
Pages3215-3218
Number of pages4
DOIs
StatePublished - 2012
Externally publishedYes
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: 28 Aug 20121 Sep 2012

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
Country/TerritoryUnited States
CitySan Diego, CA
Period28/08/121/09/12

Keywords

  • deformable model
  • Image cosegmentation
  • Magnetic resonance imaging

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