Modeling the orientation distribution function by mixtures of angular central Gaussian distributions
Please always quote using this URN:urn:nbn:de:0296-matheon-7319
- In this paper we develop a tensor mixture model for diffusion weighted imaging data using an automatic model selection criterion for the order of tensor components in a voxel. We show that the weighted orientation distribution function for this model can be expanded into a mixture of angular central Gaussian distributions. We show properties of this model in extensive simulations and in a high angular resolution experimental data set. The results suggest that the model may improve imaging of cerebral fiber tracts. We demonstrate how inference on canonical model parameters may give rise to new clinical applications.
Author: | Karsten Tabelow, Henning U. Voss, Jörg Polzehl |
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URN: | urn:nbn:de:0296-matheon-7319 |
Referee: | Konrad Polthier |
Document Type: | Preprint, Research Center Matheon |
Language: | English |
Date of first Publication: | 2010/11/17 |
Release Date: | 2010/11/15 |
Preprint Number: | 741 |