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Deformable image registration by combining uncertainty estimates from supervoxel belief propagation

Abstract:

Discrete optimisation strategies have a number of advantages over their continuous counterparts for deformable registration of medical images. For example: it is not necessary to compute derivatives of the similarity term; dense sampling of the search space reduces the risk of becoming trapped in local optima; and (in principle) an optimum can be found without resorting to iterative coarse-to-fine warping strategies. However, the large complexity of high-dimensional medical data renders a ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.media.2015.09.005

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Department:
Deptartment of Oncology
Role:
Author
Engineering and Physical Sciences Research Council More from this funder
Cancer Research UK More from this funder
Publisher:
Elsevier Publisher's website
Journal:
Medical Image Analysis Journal website
Volume:
27
Pages:
57-71
Publication date:
2015-10-19
Acceptance date:
2015-09-22
DOI:
ISSN:
1361-8415
Source identifiers:
578866
Keywords:
Pubs id:
pubs:578866
UUID:
uuid:49749a6f-4b05-4999-99d4-ae4f4ceb7d8d
Local pid:
pubs:578866
Deposit date:
2015-12-08

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