Magnetic Particle Imaging (MPI) is capable of capturing fast dynamic processes in 3D volumes, based on the non-linear response of the magnetic nanoparticles to an applied magnetic field. The image reconstruction is computationally demanding due to a non-sparse system matrix. In this study we propose a quadratic spatio-temporal regularization that can be efficiently solved. Results are presented for simulated and experimental measurement data.

This presentation is part of Minisymposium “MS56 - Mathematical and Computational Aspects in Magnetic Particle Imaging (2 parts)”
organized by: Tobias Kluth (University of Bremen) , Christina Brandt (University of Hamburg) .

Authors:

Andreas Hauptmann (University College London)

Christina Brandt (University of Hamburg)

Keywords:

dynamic imaging, image reconstruction, inverse problems, nonlinear optimization