A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions

Navid Shiee, Pierre Louis Bazin, Arzu Ozturk, Daniel S. Reich, Peter A. Calabresi, Dzung L. Pham

Research output: Contribution to journalArticle

213 Scopus citations

Abstract

We describe a new fully automatic method for the segmentation of brain images that contain multiple sclerosis white matter lesions. Multichannel magnetic resonance images are used to delineate multiple sclerosis lesions while segmenting the brain into its major structures. The method is an atlas-based segmentation technique employing a topological atlas as well as a statistical atlas. An advantage of this approach is that all segmented structures are topologically constrained, thereby allowing subsequent processing such as cortical unfolding or diffeomorphic shape analysis techniques. Evaluation with both simulated and real data sets demonstrates that the method has an accuracy competitive with state-of-the-art MS lesion segmentation methods, while simultaneously segmenting the whole brain.

Original languageEnglish (US)
Pages (from-to)1524-1535
Number of pages12
JournalNeuroImage
Volume49
Issue number2
DOIs
StatePublished - Jan 15 2010

Keywords

  • Fuzzy segmentation
  • Lesion segmentation
  • Multiple sclerosis
  • Topology

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

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    Shiee, N., Bazin, P. L., Ozturk, A., Reich, D. S., Calabresi, P. A., & Pham, D. L. (2010). A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions. NeuroImage, 49(2), 1524-1535. https://doi.org/10.1016/j.neuroimage.2009.09.005