Title:
Tubular Fiber Bundles Segmentation for Diffusion Weighted Images
Tubular Fiber Bundles Segmentation for Diffusion Weighted Images
Author(s)
Niethammer, Marc
Zach, Christopher
Melonakos, John
Tannenbaum, Allen R.
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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Date Issued
2008-09-10
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Text
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Proceedings