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Thesis

Bayesian learning methods for modelling functional MRI

Abstract:

Bayesian learning methods are the basis of many powerful analysis techniques in neuroimaging, permitting probabilistic inference on hierarchical, generative models of data. This thesis primarily develops Bayesian analysis techniques for magnetic resonance imaging (MRI), which is a noninvasive neuroimaging tool for probing function, perfusion, and structure in the human brain.

The first part of this work fits nonlinear biophysical models to multimodal functional MRI data within a v...

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Institution:
University of Oxford
Research group:
FMRIB Centre
Oxford college:
Balliol College
Role:
Author

Contributors

Division:
MSD
Department:
Clinical Neurosciences
Role:
Supervisor
Division:
MSD
Department:
Clinical Neurosciences
Role:
Supervisor
Publication date:
2009
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
Oxford University, UK
Language:
English
Keywords:
Subjects:
UUID:
uuid:fe46e696-a1a6-4a9d-9dfe-861b05b1ed33
Local pid:
ora:11622
Deposit date:
2015-06-10

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