Dynamic retrospective filtering of physiological noise in BOLD fMRI: DRIFTER

Abstract

In this article we introduce the DRIFTER algorithm, which is a new model based Bayesian method for retrospective elimination of physiological noise from functional magnetic resonance imaging (fMRI) data. In the method, we first estimate the frequency trajectories of the physiological signals with the interacting multiple models (IMM) filter algorithm. The… (More)
DOI: 10.1016/j.neuroimage.2012.01.067

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