Using anisotropic diffusion of probability maps for activity detection in block-design functional MRI
A new approach for improving the detection of pixels associated with neural activity in functional magnetic resonance imaging (fMRI) is presented. We propose to use anisotropic diffusion to exploit the spatial correlation between the active pixels in functional MRI. Specifically, in this paper the anisotropic diffusion flow is applied to a probability image, obtained either from t-map statistics or via Bayes rule. In general, this information diffusion technique can be incorporated into other activity detection algorithms before the active/non-active hard decision is made. Examples with simulated and real data show improvements over classical techniques.