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

Li Wang, Feng Shi, Gang Li, Dinggang Shen

    Research output: Contribution to journalArticlepeer-review

    22 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

    ASJC Scopus subject areas

    • General

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