86 citations · 265 across the 18 of their papers we have counts for
18 papers
Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging
Meira Iske, Hannes Albers, Tobias Knopp +1
Magnetic Particle Imaging (MPI) is an emerging imaging modality based on the magnetic response of superparamagnetic iron oxide nanoparticles to achieve high-resolution and real-tim…
Data-driven approaches for electrical impedance tomography image segmentation from partial boundary data
Alexander Denker, Zeljko Kereta, Imraj Singh +4
Electrical impedance tomography (EIT) plays a crucial role in non-invasive imaging, with both medical and industrial applications. In this paper, we present three data-driven recon…
Equilibrium Model with Anisotropy for Model-Based Reconstruction in Magnetic Particle Imaging
Marco Maass, Tobias Kluth, Christine Droigk +4
Magnetic particle imaging is a tracer-based tomographic imaging technique that allows the concentration of magnetic nanoparticles to be determined with high spatio-temporal resolut…
Bayesian view on the training of invertible residual networks for solving linear inverse problems
Clemens Arndt, Sören Dittmer, Nick Heilenkötter +3
Learning-based methods for inverse problems, adapting to the data's inherent structure, have become ubiquitous in the last decade. Besides empirical investigations of their often r…
Time-dependent parameter identification in a Fokker-Planck equation based magnetization model of large ensembles of nanoparticles
Hannes Albers, Tobias Kluth
In this article, we consider a model motivated by large ensembles of nanoparticles' magnetization dynamics using the Fokker-Planck equation and analyze the underlying parabolic PDE…
Learning-based approaches for reconstructions with inexact operators in nanoCT applications
Tom Lütjen, Fabian Schönfeld, Alice Oberacker +4
Imaging problems such as the one in nanoCT require the solution of an inverse problem, where it is often taken for granted that the forward operator, i.e., the underlying physical…