RFASTfMRI-package: FAST Adaptive Smoothing and Thresholding for Improved...

Description Maintainer Author(s) References


Functional Magnetic Resonance Imaging is a noninvasive tool used to study brain function. Detecting activation is challenged by many factors, and even more so in low-signal scenarios that arise in the performance of high-level cognitive tasks. We provide a fully automated and fast adaptive smoothing and thresholding (FAST) algorithm that uses smoothing and extreme value theory on correlated statistical parametric maps for thresholding.


Israel Almodovar-Rivera <israel.almodovar@upr.edu>


Israel Almodovar-Rivera, Ranjan Maitra


Almodovar-Rivera, I., & Maitra, R. (2019). FAST adaptive smoothing and thresholding for improved activation detection in low-signal fMRI. IEEE transactions on medical imaging, 38(12), 2821-2828.

ialmodovar/RFASTfMRI documentation built on Jan. 26, 2020, 4:02 a.m.