Least-Squares Fitting of Two 3-D Point Sets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Alignment by Maximization of Mutual Information
International Journal of Computer Vision
Elastic Model Based Non-rigid Registration Incorporation Statistical Shape Information
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Model Library for Deformable Model-Based Segmentation of 3-D Brain MR-Images
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part I
Atlas-based registration parameters in segmenting sub-cortical regions from brain MRI-images
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
An enhanced version of ITK-SNAP for preoperative inspection and refinement of surface mesh models
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
Artificial enlargement of a training set for statistical shape models: application to cardiac images
FIMH'05 Proceedings of the Third international conference on Functional Imaging and Modeling of the Heart
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A novel method is proposed for elastic matching of two data volumes. A combination of mutual information, gradient information and smoothness of transformation is used to guide the deformation of another of the volumes. The deformation is accomplished in a multiresolution process by spheres containing a vector field. Position and radius of the spheres are varied. The feasibility of the method is demonstrated in two cases: matching inter-patient MR images of the head and intra-patient cardiac MR and PET images.