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Detection of Neural Activities in FMRI Using Jensen-Shannon Divergence
Jayanta Basak
Pages - 113 - 122     |    Revised - 15-09-2012     |    Published - 24-10-2012
Volume - 6   Issue - 5    |    Publication Date - October 2012  Table of Contents
Speckle Noise, Frost Filter, Fuzzy Level Set Method
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. Theoretically and experimentally we show the effectiveness of our algorithm.
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1 Barcaru, A., & Vivó-Truyols, G. (2016). Use of Bayesian Statistics for Pairwise Comparison of Megavariate Data Sets: Extracting Meaningful Differences between GCxGC-MS Chromatograms Using Jensen–Shannon Divergence. Analytical chemistry, 88(4), 2096-2104.
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Dr. Jayanta Basak
NetApp - India