Nonrigid Registration Using Regularized Matching Weighted by Local Structure

Authors:
Eduardo Suárez;Carl-Fredrik Westin;Eduardo Rovaris;Juan Ruiz-Alzola
Affiliations:
-;-;-;-
Venue:
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part II
Year:
2002

Citing 2
Cited 1

Computational vision and regularization theory

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Abstract

We present a novel approach to nonrigid registration of volumetric multimodal medical data. We propose a new regularized template matching scheme, where arbitrary similarity measures can be embedded and the regularization imposes spatial coherence taking into account the quality of the matching according to an estimation of the local structure. We propose to use an efficient variation of weighted least squares termed normalized convolution as a mathematically coherent framework for the whole approach. Results show that our method is fast as accurate.