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We address the problem of segmenting high angular resolution diffusion images of the brain into cerebral regions corresponding to distinct white matter fiber bundles. We cast this problem as a manifold clustering problem in which distinct fiber bundles correspond to different submanifolds of the space of orientation distribution functions (ODFs). Our approach integrates tools from sparse representation...
Image matting deals with the estimation of the alpha matte at each pixel, i.e., the contribution of the foreground and background objects to the composition of the image at that pixel. Existing methods for image matting are typically limited to estimating the alpha mattes for two image layers only. However, in several applications one is interested in editing images with multiple objects. In this...
High angular resolution diffusion imaging has become an important magnetic resonance technique for in vivo imaging. Most current research in this field focuses on developing methods for computing the orientation distribution function (ODF), which is the probability distribution function of water molecule diffusion along any angle on the sphere. In this paper, we present a Riemannian framework to carry...
We propose a scheme to introduce directionality in the random walker algorithm for image segmentation. In particular, we extend the optimization framework of this algorithm to combinatorial graphs with directed edges. Our scheme is interactive and requires the user to label a few pixels that are representative of a foreground object and of the background. These labeled pixels are used to learn intensity...
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