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Abstract #2271

Determination of the Point Spread Function for Compressed Sensing Reconstruction

Iulius Dragonu1, Guobin Li1, Jeff Snyder1, Jrgen Hennig1, Maxim Zaitsev1

1Dept. of Radiology, Medical Physics, University Medical Center Freiburg, Freiburg, Germany

Compressed Sensing (CS) is a technique that allows accelerating data acquisition in the presence of sparse or compressible signals. This is accomplished by using a pseudo-random undersampling in the phase-encoding direction. The Point Spread Function (PSF) is a fundamental tool allowing the evaluation of the quality of reconstruction and the spatial resolution of images. Previously the concept of PSF approximation was extended to non-linear and non-stationary imaging systems. The PSF has different values in all imaging points due to the non-linearity and non-stationary proprieties of the CS algorithms. In this work, we propose a technique of evaluating the PSF of the CS reconstruction based on an acquisition pattern used in PSF for echo-planar imaging.