Optimal Transport for Diffeomorphic Registration

Abstract : 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.
Complete list of metadatas

Cited literature [15 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01540455
Contributor : Gabriel Peyré <>
Submitted on : Friday, June 16, 2017 - 12:54:10 PM
Last modification on : Tuesday, May 28, 2019 - 1:54:03 PM
Long-term archiving on : Wednesday, December 13, 2017 - 12:41:32 PM

Files

MICAI2017.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01540455, version 1
  • ARXIV : 1706.05218

Citation

Jean Feydy, Benjamin Charlier, François-Xavier Vialard, Gabriel Peyré. Optimal Transport for Diffeomorphic Registration. MICCAI 2017, Sep 2017, Quebec, Canada. ⟨hal-01540455⟩

Share

Metrics

Record views

1305

Files downloads

855