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Digital Object Identifier (DOI) : 10.14569/IJACSA.2016.070143
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 1, 2016.
Abstract: In the functional Magnetic Resonance Imaging (fMRI) data analysis, detecting the activated voxels is a challenging research problem where the existing methods have shown some limits. We propose a new method wherein brain mapping is done based on Dempster-Shafer theory of evidence (DS) that is a useful method in uncertain representation analysis. Dempster-Shafer allows finding the activated regions by checking the activated voxels in fMRI data. The activated brain areas related to a given stimulus are detected by using a belief measure as a metric for evaluating activated voxels. To test the performance of the proposed method, artificial and real auditory data have been employed. The comparison of the introduced method with the t-test and GLM method has clearly shown that the proposed method can provide a higher correct detection of activated voxels.
ATTIA Abdelouahab, MOUSSAOUI Abdelouahab and TALEB-AHMED Abdelmalik, “fMRI Data Analysis Using Dempster-Shafer Method with Estimating Voxel Selectivity by Belief Measure” International Journal of Advanced Computer Science and Applications(IJACSA), 7(1), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070143