Registration of anatomical images using geodesic paths of diffeomorphisms parameterized with stationary vector fields

Monica Hernandez, Matias N. Bossa, Salvador Olmos

Research output: Chapter in Book/Report/Conference proceedingConference paperResearch

21 Citations (Scopus)

Abstract

Computational Anatomy aims for the study of the statistical variability in anatomical structures. Variability is encoded by the transformations existing among populations of anatomical images. These transformations are usually computed from diffeomorphic registration based on the large deformation paradigm. In this framework diffeomorphisms are usually computed as end points of paths on the Riemannian manifold of diffeomorphisms parameterized by nonstationary vector fields. Recently, an alternative parameterization based on stationary vector fields has been developed. In this article we propose to use this stationary parameterization for diffeomorphic registration. We formulate the variational problem related to this registration scenario and derive the associated Euler-Lagrange equations. We evaluate the performance of the non-stationary vs the stationary parameterizations in real and synthetic 3D-MRI datasets. Compared to the non-stationary parameterization, our proposal provides similar accuracy in terms of image matching and deformation smoothness while drastically reducing memory and time requirements.

Original languageEnglish
Title of host publication2007 IEEE 11th International Conference on Computer Vision
DOIs
Publication statusPublished - 1 Dec 2007
Event2007 IEEE 11th International Conference on Computer Vision, ICCV - Rio de Janeiro, Brazil
Duration: 14 Oct 200721 Oct 2007

Conference

Conference2007 IEEE 11th International Conference on Computer Vision, ICCV
Country/TerritoryBrazil
CityRio de Janeiro
Period14/10/0721/10/07

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