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MICCAI
2010
Springer

Multi-Diffusion-Tensor Fitting via Spherical Deconvolution: A Unifying Framework

10 years 9 months ago
Multi-Diffusion-Tensor Fitting via Spherical Deconvolution: A Unifying Framework
Abstract. 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 reliable approximative fit that is efficiently refined by a subsequent descent-type optimization. Moreover, deciding on the number of fibers based on the orientation distribution function produces favorable results when compared to the traditional F-Test. Our work demonstrates the benefits of unifying previously divergent lines of work in diffusion image analysis.
Thomas Schultz, Carl-Fredrik Westin, Gordon L. Kin
Added 14 Feb 2011
Updated 14 Feb 2011
Type Journal
Year 2010
Where MICCAI
Authors Thomas Schultz, Carl-Fredrik Westin, Gordon L. Kindlmann
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