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Diffusion tensor magnetic resonance imaging is a newly developed imaging technique; however, this technique is noise sensitive. This paper presents a novel method for sparse representation denoising of MR images that propose sparse representation of the corrupted images with the knowledge of the Rician noise model. The proposed model inferring the prior that MR images are composed of several separated...
Tracking linear features through tensor field datasets is an open research problem with widespread utility in medical and engineering disciplines. Existing tracking methods, which consider only the preferred local diffusion direction as they propagate, fail to accurately follow features as they enter regions of local complexity. This shortcoming is a result of partial voluming; that is, voxels in...
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