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A Bayesian framework for global tractography.

Abstract:

We readdress the diffusion tractography problem in a global and probabilistic manner. Instead of tracking through local orientations, we parameterise the connexions between brain regions at a global level, and then infer on global and local parameters simultaneously in a Bayesian framework. This approach offers a number of important benefits. The global nature of the tractography reduces sensitivity to local noise and modelling errors. By constraining tractography to ensure a connexion is fou...

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Publication status:
Published

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Institution:
University of Oxford
Department:
Oxford, MSD, Clinical Neuroscience
Role:
Author
More by this author
Institution:
University of Oxford
Department:
Oxford, MSD, Psychiatry
Role:
Author
More by this author
Institution:
University of Oxford
Department:
Oxford, MSD, Clinical Neuroscience, Experimental Psychology
Role:
Author
Journal:
NeuroImage
Volume:
37
Issue:
1
Pages:
116-129
Publication date:
2007-08-05
DOI:
EISSN:
1095-9572
ISSN:
1053-8119
URN:
uuid:427abdfc-f7a7-41f4-8446-b6b2b1f9f508
Source identifiers:
28894
Local pid:
pubs:28894

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