Abstract #0463

Unsupervised Correction of Sub-TR Physiological Noise using Phase and Magnitude fMRI data

David Bancelin¹, Beata Bachrata^1,2, Pedro Lima Cardoso¹, Siegfried Trattnig^1,2, and Simon Daniel Robinson^1,3,4

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

External physiological recordings can be used to filter out cardiac and respiration fluctuations in fMRI data but these can be unreliable. We propose an unsupervised method which derives physiological noise regressors, including cardiac fluctuations with a period much less than the volume TR, from phase and magnitude fMRI data. We compare its efficacy with a correction method which uses external recordings (RETROICOR), and a rival physiological data-free method (PESTICA).

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