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.
|Author||Israel Almodovar-Rivera, Ranjan Maitra|
|Maintainer||Israel Almodovar-Rivera <firstname.lastname@example.org>|
|Package repository||View on GitHub|
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