Registration of functional magnetic resonance imagery using mutual information

Abstract
Accurate statistical correlation of brain activation in functional magnetic resonance image (MRI) studies depends on the reduction of artifacts induced by patient motion. We have addressed this problem in two ways. First, we have eliminated gross movement by the development of an immobilization mask. Second, we have implemented the image registration procedure, mutual information. This registration procedure is used to correct remaining misalignments due to patient motion. We have chosen maximization of mutual information because it is applicable to a broad range of image registration problems because it requires no segmentation, feature extraction, a priori information, or operator-assisted extractions. Initial results, as applied to fMRI data, are also presented. Our results indicate that we have reduced the motion artifacts present in our original data sets with sub-voxel accuracy.

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