MUTUAL INFORMATION BASED IMAGE PROCESSING FOR FMRI

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This project aims primarily to further develop and evaluate a novel method for the detection of activation in functional Magnetic Resonance Images (fMRI). Standard approaches to the detection of activation are described, as well as the clinical significance of detection results for neurosurgical planning. The new method is based on a formulation of the mutual information between two waveforms--the fMRI temporal response of a voxel and the experimental protocol timeline. In this method, scores based on mutual information are generated for all voxels and then used to compute the activation map of an experiment. Mutual information for fMRI analysis is employed because it has been shown to be robust in quantifying the relationship between any two waveforms. Our technique takes a principled approach toward calculating the brain activation map by making few assumptions about the relationship between the protocol timeline and the temporal response of a voxel. This may be significant in fMRI experiments where little is known about the relationship between these two waveforms. Preliminary experiments are presented to demonstrate this approach of computing the brain activation map, and a comparison to other more traditional analysis techniques is presented. A plan is described to obtain representative data sets from ongoing projects and to use them for a comparison of the new method and a standard method.