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.
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