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    Tubular Fiber Bundles Segmentation for Diffusion Weighted Images

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    2008_miccai_04.pdf (362.8Kb)
    Date
    2008-09-10
    Author
    Niethammer, Marc
    Zach, Christopher
    Melonakos, John
    Tannenbaum, Allen R.
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    Abstract
    This paper proposes a methodology to segment tubular fiber bundles from diffusion weighted magnetic resonance images (DW-MRI). Segmentation is simplified by locally reorienting diffusion information based on large-scale fiber bundle geometry. Segmentation is achieved through simple global statistical modeling of diffusion orientation. Utilizing a modification of a recent segmentation approach by Bresson et al. [19] allows for a convex optimization formulation of the segmentation problem, combining orientation statistics and spatial regularization. The approach compares favorably with segmentation by full-brain streamline tractography.
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    http://hdl.handle.net/1853/29317
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    • Biomedical Imaging Lab (Minerva Research Group) [210]

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