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Abstract #2299

2D Matched Filter Acquisition for Improved SNR in Routine Brain Imaging

Lars Kasper1, 2, Maximilian Haeberlin1, Bertram Jakob Wilm1, Klaas Enno Stephan2, 3, Klaas Paul Pruessmann1

1ETH/UZH Zurich, Institute for Biomedical Engineering, Zurich, Switzerland; 2University of Zurich, Laboratory for Social and Neural Systems Research, Zurich, Switzerland; 3University College London, Wellcome Trust Centre for Neuroimaging, London, United Kingdom

MR images are commonly processed after image reconstruction, e.g. to suppress Gibbs ringing artifacts. Following the matched filter theorem, we optimize a regular gradient echo acquisition to maximize the signal-to-noise ratio (SNR) in the final, smoothed images. Our approach enables a 2D-matching of the acquisition to the desired smoothing filter by combining variable phase encoding line spacing with gradient amplitude modulation in readout direction. This doubles the benefits of a matched filter acquisition compared to sole 1D-matching of the desired smoothing kernels yielding SNR increases of up to 50 %.