Abstract #2729

Prospective SNR Optimization in k-T-Based Sensitivity-Encoded Dynamic Imaging Using a Fast Geometric Algorithm

Behzad Sharif¹, John Andrew Derbyshire², Yoram Bresler¹

¹Coordinated Science Lab, Department of Electrical & Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA; ²Cardiovascular Branch, NHLBI, National Institutes of Health, DHHS, Bethesda, MD, USA

The acceleration in k-t-based dynamic parallel imaging results from multi-fold undersampling (relative to the Nyquist rate) provided by the k-t sampling scheme. Such sampling results in aliasing of the signal spectrum in the reciprocal domain (x-f space). We propose a novel algorithm for prospective design of SNR-optimal k-t sampling patterns and study its performance in-vivo for real-time cardiac parallel imaging. All computations are based on geometry of overlap patterns in x-f space and are independent of coil sensitivities. This