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Abstract #1625

Frequency offset correction for accelerated 3D-EPI with segmented reference data

Martina F Callaghan1, Nad├Ęge Corbin1, Marina Papoutsi2, Nikolaus Weiskopf1,3, and Oliver Josephs1

1Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, United Kingdom, 2Huntington's Disease Research Centre, Institute of Neurology, UCL, London, United Kingdom, 3Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

3D-EPI is beneficial for real-time fMRI applications because the acquisition can be accelerated in both the in-plane and through-plane phase-encoded directions significantly increasing temporal resolution. Fully-sampled reference data are required in order to map coil sensitivities and unfold the aliased images that result. Acquiring these data with a segmented EPI readout matches the EPI-related distortions and dropouts between the un-accelerated reference data and the accelerated fMRI data. However, systematic differences in eddy-current-related phase between the segments can introduce errors during frequency offset correction (employed to correct for slow frequency drifts) unless accounted for. Here we present a simple correction scheme that greatly improves the tSNR of the time series.

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