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

@article{Abdelouahab2016,
title = {fMRI Data Analysis Using Dempster-Shafer Method with Estimating Voxel Selectivity by Belief Measure},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070143},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070143},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {1},
author = {ATTIA Abdelouahab and MOUSSAOUI Abdelouahab and TALEB-AHMED Abdelmalik}
}