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 A Almodovar-Rivera and Ranjan Maitra

RFASTfMRI requires

- R version 3.0.0 or higher.
- R package fftw.

The package can be installed via the devtools package:

library(devtools)
install_github("ialmodovar/RFASTfMRI")

Almodóvar-Rivera, I., & Maitra, R. (2019). FAST adaptive smoothing and thresholding for improved activation detection in low-signal fMRI. IEEE transactions on medical imaging. doi: 10.1109/TMI.2019.2915052.