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Spatially Adaptive Log-Euclidean Polyaffine Registration based on Sparse Matches

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Taquet, Maxime [UCL] Macq, Benoît [UCL] Warfield, Simon K [Harvard Medical School]

Log-euclideanpolyaffinetransformshaverecentlybeenintro- duced to characterize the local affine behavior of the deformation in prin- cipal anatomical structures. The elegant mathematical framework makes them a powerful tool for image registration. However, their application is limited to large structures since they require the pre-definition of affine regions. This paper extends the polyaffine registration to adaptively fit a log-euclidean polyaffine transform that captures deformations at smaller scales. The approach is based on the sparse selection of matching points in the images and the formulation of the problem as an expectation max- imization iterative closest point problem. The efficiency of the algorithm is shown through experiments on inter-subject registration of brain MRI between a healthy subject and patients with multiple sclerosis.

Document type Communication à un colloque (Conference Paper) – Poster
Access type Accès libre
Publication date 2011
Language Anglais
Conference "Medical Image Computing and Computer Assisted Interventions", Toronto, Canada (du 18/09/2011 au 22/09/2011)
Host document Gabor Fichtinger, Anne Martel and Terry Peters ; "Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011"- 590–597 (ISBN : 978-3-642-23628-0)
Collection Lecture Notes in Computer Science - 6892 (ISSN : 0302-9743)
Publisher Springer-Verlag Berlin Heidelberg (Berlin)
Publication status Publié
Affiliations UCL - SST/ICTM - Institute of Information and Communication Technologies, Electronics and Applied Mathematics
Harvard Medical School - Computational Radiology Laboratory
Links
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Bibliographic reference Taquet, Maxime ; Macq, Benoît ; Warfield, Simon K. Spatially Adaptive Log-Euclidean Polyaffine Registration based on Sparse Matches.Medical Image Computing and Computer Assisted Interventions (Toronto, Canada, du 18/09/2011 au 22/09/2011). In: Gabor Fichtinger, Anne Martel and Terry Peters, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011, Springer-Verlag Berlin Heidelberg : Berlin2011, p.590–597
Permanent URL http://hdl.handle.net/2078/124675