Evaluation of Systematic and Statistical Reconstruction Errors in Compressed Sensing Reconstructions

Daniel Stb¹, Tobias Wech¹, Dietbert Hahn¹, Herbert Kstler¹

In CS, metrics for evaluating the image quality are hardly available. In this work, a simple Monte Carlo approach is presented that allows evaluating systematic and statistical reconstruction errors. Based on a fully sampled reference acquisition and a noise measurement, multiple pseudo measurements are synthesized. By comparing their reconstructions to the reference, systematic signal deviations can be quantified. In addition, the extent of statistical fluctuations can be estimated. The proposed evaluation was applied to a x-f-space CS reconstruction in myocardial perfusion MRI and systematic flattening of the signal intensity time courses was detected.