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 <email@example.com>
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.
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