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Lecture Notes in Computer Science
In analyzing diffusion magnetic resonance imaging, multitensor models address the limitations of the single diffusion tensor in situations of partial voluming and fiber crossings. However, selection of a suitable number of fibers and numerical difficulties in model fitting have limited their practical use. This paper addresses both problems by making spherical deconvolution part of the fitting process: We demonstrate that with an appropriate kernel, the deconvolution provides a reliabledoi:10.1007/978-3-642-15705-9_82 fatcat:wqumevnsvfge7fdbgc7pp53im4