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Probabilistic inference of regularisation in non-rigid registration.

Abstract:

A long-standing issue in non-rigid image registration is the choice of the level of regularisation. Regularisation is necessary to preserve the smoothness of the registration and penalise against unnecessary complexity. The vast majority of existing registration methods use a fixed level of regularisation, which is typically hand-tuned by a user to provide "nice" results. However, the optimal level of regularisation will depend on the data which is being processed; lower signal-to-noise ratio...

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Publication status:
Published

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Authors


Simpson, IJ More by this author
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Institution:
University of Oxford
Department:
Oxford, MPLS, Engineering Science
More by this author
Institution:
University of Oxford
Department:
Oxford, MSD, Clinical Neurosciences
Andersson, JL More by this author
More by this author
Institution:
University of Oxford
Department:
Oxford, MSD, Psychiatry
Journal:
NeuroImage
Volume:
59
Issue:
3
Pages:
2438-2451
Publication date:
2012-02-05
DOI:
EISSN:
1095-9572
ISSN:
1053-8119
URN:
uuid:52cc7bba-0161-411f-8fc4-b02eafb8888e
Source identifiers:
180435
Local pid:
pubs:180435

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