Parameter robustness analysis for system function reconstruction

Abstract

The quality of images in system function reconstruction (SFR) depends on an extensive calibration scan that acquires the system matrix (SM). A change in parameters of the scanner, trajectory, or magnetic nanoparticle requires the acquisition of a new SM. In this work, we analyze the parameter robustness of SFR with simulations. We investigate the effect of utilizing an existing SM in the case of a change in the aforementioned parameters. The results show that a new calibration scan is not needed, as long as the change is sufficiently small.