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Abstract #4007

Correcting respiratory-related noise in brainstem fMRI using regressors derived from phase data

David Bancelin1, Pedro Lima Cardoso1, Beata Bachrata1,2, Andreas Ehrmann1, Siegfried Trattnig1,2, and Simon D. Robinson1,3,4
1High-Field MR Centre, Medical University of Vienna, Vienna, Austria, 2Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria, 3Department of Neurology, Medical University of Graz, Graz, Austria, 4Centre for Advanced Imaging, University of Queensland, Queensland, Australia

Respiratory and cardiac data are generally used to properly account for the presence of physiological noise in fMRI data. Pneumatic belts can be unreliable, but we show that EPI phase data can be used to generate a reliable respiratory time series from which regressors are used in a GLM procedure to correct magnitude data. The efficacy of our method is compared with respect to (i) uncorrected magnitude data and (ii) magnitude data corrected using respiratory belt-derived regressors.

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