Curvature Based Registration with Applications to MR-Mammography

Authors:
Bernd Fischer;Jan Modersitzki
Affiliations:
-;-
Venue:
ICCS '02 Proceedings of the International Conference on Computational Science-Part III
Year:
2002

Citing 5
Cited 0

Multiresolution elastic matching

Computer Vision, Graphics, and Image Processing
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
Fast Fluid Registration of Medical Images

VBC '96 Proceedings of the 4th International Conference on Visualization in Biomedical Computing
Optimal registration of deformed images

Optimal registration of deformed images

Quantified Score

Hi-index	0.01

Visualization

Abstract

We introduce a new non-linear registration model based on a curvature type regularizer. We show that affine linear transformations belong to the kernel of this regularizer. Consequently, an additional global registration is superfluous. Furthermore, we present an implementation of the new scheme based on the numerical solution of the underlying Euler-Lagrange equations. The real discrete cosine transform is the backbone of our implementation and leads to a stable and fast O(nlogn) algorithm, where n denotes the number of voxels. We demonstrate the advantages of the new technique for synthetic data sets. Moreover, first convincing results for the registration of MR-mammography images are presented.