fMRI Data Analysis Using Dempster-Shafer Method with Estimating Voxel Selectivity by Belief Measure
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 1
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.
Authors and Affiliations
ATTIA Abdelouahab, MOUSSAOUI Abdelouahab, TALEB-AHMED Abdelmalik
Keywords
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- EP ID EP143647
- DOI 10.14569/IJACSA.2016.070143
- Views 108
- Downloads 0
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