Magnetic particle imaging (MPI) is a new imaging modality to determine the concentration of nanoparticles from their nonlinear magnetization behavior. Highly dynamic applied magnetic fields allow a rapid data acquisition in 3D. But the image reconstruction still relies on a time-consuming calibration process. The large model uncertainty is a great challenge for achieving reconstructions with higher resolution. In this mini-symposium, we aim at bringing together researchers working on magnetic particle imaging and related fields. We cover theoretical and practical topics in MPI focusing on mathematical and physical as well as algorithmic and computational issues of the reconstruction.

Mathematical models in magnetic particle imaging (MPI)

Tobias Kluth (University of Bremen)

Modeling the system function in MPI

Anne Wald (Saarland University)

Time-Frequency-Preprocessing of MPI Raw Signals

Florian Lieb (University of Applied Sciences, Aschaffenburg)

Model-based reconstruction for multivariate MPI

Andreas Weinmann (Hochschule Darmstadt)

Fast Image Reconstruction by Exploiting Redundancies and Sparsities in the Magnetic Particle Imaging Operator

Knopp Tobias (University Medical Center Hamburg-Eppendorf/Hamburg University of Technology)

Fast temporal regularized reconstructions for magnetic particle imaging

Andreas Hauptmann (University College London)

Edge preserving and noise reducing reconstruction for magnetic particle imaging

Martin Storath (Universität Heidelberg)

Organizers:

Christina Brandt (University of Hamburg)

Tobias Kluth (University of Bremen)

Keywords:

image reconstruction, inverse problems