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.

• Type: Journal
• Year: 2010
• Where: MICCAI
• Authors: Thomas Schultz, Carl-Fredrik Westin, Gordon L. Kindlmann
• Keywords: Diffusion Magnetic Resonance, Fibers, Medical Imaging, MICCAI 2010, Single Diffusion Tensor