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Thesis

Bayesian statistical models of shape and appearance for subcortical brain segmentation

Abstract:

Our motivation is to develop an automated technique for the segmentation of sub-cortical human brain structures from MR images. To this purpose, models of shape-and-appearance are constructed and fit to new image data. The statistical models are trained from 317 manually labelled T1-weighted MR images. Shape is modelled using a surface-based point distribution model (PDM) such that the shape space is constrained to the linear combination of the mean shape and eigenvectors of the vertex coo...

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Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Research group:
FMRIB
Oxford college:
Worcester College
Role:
Author

Contributors

Role:
Supervisor
Role:
Supervisor
Publication date:
2007
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford
Language:
English
Keywords:
Subjects:
UUID:
uuid:52f5fee0-60e8-4387-9560-728843e187b3
Local pid:
ora:8408
Deposit date:
2014-05-12

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