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Detection of Neural Activities in FMRI Using Jensen-Shannon Divergence
In this paper, we present a statistical technique based on Jensen-Shanon divergence for detecting the regions of activity in fMRI images. The method is model free and we exploit the metric property of the square root of Jensen-Shannon divergence to accumulate the variations between successive time frames of fMRI images. Experimentally we show the effectiveness of our algorithm.
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