4D Segmentation of Brain MR Images with Constrained Cortical Thickness Variation

Li Wang, Feng Shi, Gang Li, Dinggang Shen

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Segmentation of brain MR images plays an important role in longitudinal investigation of developmental, aging, disease progression changes in the cerebral cortex. However, most existing brain segmentation methods consider multiple time-point images individually and thus cannot achieve longitudinal consistency. For example, cortical thickness measured from the segmented image will contain unnecessary temporal variations, which will affect the time related change pattern and eventually reduce the statistical power of analysis. In this paper, we propose a 4D segmentation framework for the adult brain MR images with the constraint of cortical thickness variations. Specifically, we utilize local intensity information to address the intensity inhomogeneity, spatial cortical thickness constraint to maintain the cortical thickness being within a reasonable range, and temporal cortical thickness variation constraint in neighboring time-points to suppress the artificial variations. The proposed method has been tested on BLSA dataset and ADNI dataset with promising results. Both qualitative and quantitative experimental results demonstrate the advantage of the proposed method, in comparison to other state-of-the-art 4D segmentation methods.

Original languageEnglish
Article numbere64207
JournalPLoS One
Volume8
Issue number7
DOIs
Publication statusPublished - 2013 Jul 2

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Brain
brain
Aging of materials
cerebral cortex
methodology
disease course
Cerebral Cortex
temporal variation
Disease Progression
Datasets

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

4D Segmentation of Brain MR Images with Constrained Cortical Thickness Variation. / Wang, Li; Shi, Feng; Li, Gang; Shen, Dinggang.

In: PLoS One, Vol. 8, No. 7, e64207, 02.07.2013.

Research output: Contribution to journalArticle

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