Regularization of inverse visual problems involving discontinuities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Principal Warps: Thin-Plate Splines and the Decomposition of Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Three-Dimensional Surface Reconstruction Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image warping by radial basis functions: applications to facial expressions
CVGIP: Graphical Models and Image Processing
Registration of 3D multi-modality medical images using surfaces and point landmarks
VIP '94 The international conference on volume image processing on Volume image processing
Deformations incorporating rigid structures
Computer Vision and Image Understanding
A Framework for Uncertainty and Validation of 3-D RegistrationMethods Based on Points and Frames
International Journal of Computer Vision
Landmark-Based Image Analysis: Using Geometric and Intensity Models
Landmark-Based Image Analysis: Using Geometric and Intensity Models
Snakes and Splines for Tracking Non-Rigid Heart Motion
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Point-Based Elastic Registration of Medical Image Data Using Approximating Thin-Plate Splines
VBC '96 Proceedings of the 4th International Conference on Visualization in Biomedical Computing
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
A New Class of Elastic Body Splines for Nonrigid Registration of Medical Images
Journal of Mathematical Imaging and Vision
Differential Evolution as a viable tool for satellite image registration
Applied Soft Computing
A robust hybrid method for nonrigid image registration
Pattern Recognition
Incorporating rigid structures in non-rigid registration using triangular b-splines
VLSM'05 Proceedings of the Third international conference on Variational, Geometric, and Level Set Methods in Computer Vision
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We introduce a spline-based elastic registration scheme which is based on a well-defined minimizing functional for which the solution can be stated analytically. In this work, we consider the integration of anisotropic landmark errors as well as additional attributes at landmarks. As attributes we use orientations at landmarks and we incorporate the corresponding constraints through scalar products. With our approximation scheme it is thus possible to integrate statistical as well as geometric information as additional knowledge in elastic image registration. On the basis of synthetic as well as real tomographic images we show that this additional knowledge can significantly improve the registration result. In particular, we demonstrate that our scheme incorporating orientation attributes can preserve the shape of rigid structures (such as bone) embedded in an otherwise elastic material. This is achieved without selecting further landmarks and without a full segmentation of the rigid structures.