Maximum entropy spherical deconvolution for diffusion MRI

Authors:
Daniel C. Alexander
Affiliations:
Department of Computer Science, University College London, London, UK
Venue:
IPMI'05 Proceedings of the 19th international conference on Information Processing in Medical Imaging
Year:
2005

Citing 1
Cited 13

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Abstract

This paper proposes a maximum entropy method for spherical deconvolution. Spherical deconvolution arises in various inverse problems. This paper uses the method to reconstruct the distribution of microstructural fibre orientations from diffusion MRI measurements. Analysis shows that the PASMRI algorithm, one of the most accurate diffusion MRI reconstruction algorithms in the literature, is a special case of the maximum entropy spherical deconvolution. Experiments compare the new method to linear spherical deconvolution, used previously in diffusion MRI, and to the PASMRI algorithm. The new method compares favourably both in simulation and on standard brain-scan data.