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.

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Metadaten
Author:Karsten Tabelow, Henning U. Voss, Jörg Polzehl
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
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