Singular value analysis for Magnetic Particle Imaging

Magnetic Particle Imaging (MPI) is a new imaging modality that allows to detect magnetizable nanoparticles. Recently, resolution and sensitivity of this method was investigated in a simulation study. Since the reconstruction problem in MPI is presumably ill-posed, Tikhonov regularization was applied to achieve optimal imaging quality for a certain set of acquisition parameters. The purpose of this work is to analyze the conditioning of the reconstruction problem in MPI by singular value decomposition. Considering the singular values, the ill-posedness of the reconstruction can be shown. For computing the optimal regularization parameter automatically, an algorithm is applied that exploits the L-curve.