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Optimal Transport for Diffeomorphic Registration

Feydy, Jean; Charlier, Benjamin; Vialard, François-Xavier; Peyré, Gabriel (2017), Optimal Transport for Diffeomorphic Registration, in Descoteaux M., Maier-Hein L., Franz A., Jannin P., Collins D., Duchesne S. (eds), Medical Image Computing and Computer Assisted Intervention − MICCAI 2017, Springer : Berlin Heidelberg, p. 291-299

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MICAI2017.pdf (1.822Mb)
Type
Communication / Conférence
Date
2017
Conference title
Medical Image Computing and Computer Assisted Intervention − MICCAI 2017
Conference date
2017-09
Conference city
Quebec
Conference country
Canada
Book title
Medical Image Computing and Computer Assisted Intervention − MICCAI 2017
Book author
Descoteaux M., Maier-Hein L., Franz A., Jannin P., Collins D., Duchesne S. (eds)
Publisher
Springer
Published in
Berlin Heidelberg
Pages
291-299
Metadata
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Author(s)
Feydy, Jean
Centre de Mathématiques et de Leurs Applications [CMLA]
Département de Mathématiques et Applications - ENS Paris [DMA]
Charlier, Benjamin
Institut Montpelliérain Alexander Grothendieck [IMAG]
Vialard, François-Xavier
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Peyré, Gabriel
Département de Mathématiques et Applications - ENS Paris [DMA]
Abstract (EN)
This paper introduces the use of unbalanced optimal transport methods as a similarity measure for diffeomorphic matching of imaging data. The similarity measure is a key object in diffeomorphic registration methods that, together with the regularization on the deformation, defines the optimal deformation. Most often, these similarity measures are local or non local but simple enough to be computationally fast. We build on recent theoretical and numerical advances in optimal transport to propose fast and global similarity measures that can be used on surfaces or volumetric imaging data. This new similarity measure is computed using a fast generalized Sinkhorn algorithm. We apply this new metric in the LDDMM framework on synthetic and real data, fibres bundles and surfaces and show that better matching results are obtained.
Subjects / Keywords
Diffeomorphic Registration

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