Image Registration with Guaranteed Displacement Regularity
International Journal of Computer Vision
FLIRT with Rigidity--Image Registration with a Local Non-rigidity Penalty
International Journal of Computer Vision
Optimised coupling of hierarchies in image registration
Image and Vision Computing
A semi-implicit level set method for structural shape and topology optimization
Journal of Computational Physics
A Scale-Space Approach to Landmark Constrained Image Registration
SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
Optimal discrete multi-resolution deformable image registration
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
An Optimal Control Formulation of an Image Registration Problem
Journal of Mathematical Imaging and Vision
Generalization of deformable registration in riemannian sobolev spaces
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
A preconditioning technique for a class of PDE-constrained optimization problems
Advances in Computational Mathematics
A robust multigrid approach for variational image registration models
Journal of Computational and Applied Mathematics
A scale space method for volume preserving image registration
Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
A GPU approach for accelerating 3D deformable registration (DARTEL) on brain biomedical images
Proceedings of the 20th European MPI Users' Group Meeting
A Gauss-Newton approach to joint image registration and intensity correction
Computer Methods and Programs in Biomedicine
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In this paper we introduce a new framework for image registration. Our formulation is based on consistent discretization of the optimization problem coupled with a multigrid solution of the linear system which evolves in a Gauss--Newton iteration. We show that our discretization is $h$-elliptic independent of parameter choice, and therefore a simple multigrid implementation can be used. To overcome potential large nonlinearities and to further speed up computation, we use a multilevel continuation technique. We demonstrate the efficiency of our method on a realistic highly nonlinear registration problem.