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Abstract #2226

Estimation of Mean Noise Propagation in SENSE for Generation of Optimized Undersampling Patterns

D. Nickel1, R. Grimm2, K. T. Block3

1MR Applications Development, Healthcare Sector, Siemens AG, Erlangen, Germany; 2Pattern Recognition Lab, University of Erlangen-Nuremberg, Erlangen, Germany; 3Department of Radiology, NYU Langone Medical Center, New York, United States

Incoherent undersampling of k-space is often desirable for iterative reconstruction techniques like Compressed Sensing. On the other hand, noise propagation from parallel imaging is best explored for regular undersampling patterns. Instead of focusing on the local noise enhancement in the image, typically expressed through g-factor maps, we derive an expression for the averaged noise amplification, which can be used as a measure to evaluate given undersampling patterns. Because the expression can be evaluated efficiently, it can be used during the generation of low-noise sampling patterns, mainly aiming at 3D acquisitions with incoherent undersampling in 2D.