A two-stage model-based regularized reconstruction approach for magnetic particle imaging

Magnetic Particle Imaging (MPI) is an emerging imaging modality and is currently a very active field of research. In the multivariate MPI setup images are usually reconstructed using a system matrix which is obtained by a time-consuming measurement procedure. We approach the reconstruction problem by employing a mathematical model which we introduced in an earlier work and which is based on the MPI signal encoding. Here, we present an enhanced two-stage reconstruction algorithm derived from the decomposition of the imaging process provided by the model. In the first stage of the algorithm we propose a variational formulation together with adequate regularization which improves our reconstruction results.