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Abstract #3274

k-T FASTER: A New Method for the Acceleration of Resting State fMRI Data Acquisition

Mark Chiew1, Stephen M. Smith1, Peter J. Koopmans2, Thomas Blumensath3, Karla L. Miller1

1FMRIB Centre, University of Oxford, Oxford, United Kingdom; 2Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands; 3ISVR, University of Southampton, Southampton, Hampshire, United Kingdom

In FMRI, measurements of resting state functional connectivity are often preceded by a principal component analysis to reduce data dimensionality. We propose a new method for the acceleration of FMRI acquisitions that exploits the decrease of information in a dimensionality reduction to facilitate the undersampling of k-t space. We call this approach k-t FASTER: FMRI Acceleration in Space-time via Truncation of Effective Rank. This technique is demonstrated on 4x retrospectively undersampled FMRI data to reproduce resting state networks with high spatial fidelity.