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Abstract #2252

Optimizing Random Fourier Sampling Patterns for Compressed Sensing Using Point Spread Functions

David S. Smith1, Lori R. Arlinghaus1, Thomas E. Yankeelov1, E Brian Welch1

1Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States

We show that it is possible to optimize the random sampling pattern in compressed sensing MRI using a target-independent measure before data acquisition. Despite the nonlinear and random nature of the CS reconstruction and the spatially variant PSF, we show on a T1-weighted complex image of the breast that the variance of the PSF of the sampling pattern could be a reliable predictor of the ultimate reconstruction quality. The linear correlation of the variance of the pattern PSF with the normalized mean square error of the reconstructed image was 0.55.