Nonrigid Registration Using Regularized Matching Weighted by Local Structure

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.

• Type: Conference
• Year: 2002
• Where: MICCAI
• Authors: Eduardo Suárez, Carl-Fredrik Westin, Eduardo Rovaris, Juan Ruiz-Alzola
• Keywords: Arbitrary Similarity Measures, Medical Imaging, MICCAI 2002, Normalized Convolution, Template Matching Scheme