Multiresolution elastic matching
Computer Vision, Graphics, and Image Processing
A survey of image registration techniques
ACM Computing Surveys (CSUR)
A nonlinear variational problem for image matching
SIAM Journal on Scientific Computing
Landmark-Based Image Analysis: Using Geometric and Intensity Models
Landmark-Based Image Analysis: Using Geometric and Intensity Models
Curvature Based Image Registration
Journal of Mathematical Imaging and Vision
Fast Fluid Registration of Medical Images
VBC '96 Proceedings of the 4th International Conference on Visualization in Biomedical Computing
Consistent multi-modal non-rigid registration based on a variational approach
Pattern Recognition Letters
A robust multigrid approach for variational image registration models
Journal of Computational and Applied Mathematics
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Choosing the adequate registration and simulation parameters in non-parametric image registration methods is an open question. There is no agreement about which are the optimal values (if any) for these parameters, since they depend on the images to be registered. As a result, in the literature the parameters involved in the registration process are arbitrarily fixed by the authors. The present paper is intended to address this issue. A two-step method is proposed to obtain the optimal values of these parameters, in terms of achieving in a minimum number of iterations the best trade-off between similarity of the images and smoothness of the transformation. These optimal values minimize the joint energy functional defined in a variational framework. We focus on the specific formulation of diffusion and curvature registration, but the exposed methodology can be directly applied to other non-parametric registration schemes. The proposed method is validated over different registration scenarios.