Local Temporal Point Spread Function for CS Reconstructions Exploiting X-F-Sparsity

Tobias Wech¹, Daniel Stb¹, Andre Fischer¹, Dietbert Hahn¹, Herbert Kstler¹

Compressed Sensing reconstructions exploiting spatio-temporal sparsity have successfully been applied to accelerate dynamic MRI. However, the non-linear and non-stationary CS algorithms prohibit the straightforward evaluation of the temporal resolution through a single global temporal point spread function. In this work a pixelwise perturbation strategy was utilized to assess local temporal point spread functions for every image pixel. The method therefore allows an appropriate assessment of the temporal resolution and can thus improve the choice of sampling patterns and algorithm settings.