The classic regularization theory for solving inverse problems is built on the assumption that
the forward operator perfectly represents the underlying physical model of the data …

Various imaging modalities allow for time-dependent image reconstructions from
measurements where its acquisition also has a time-dependent nature. Magnetic particle …

Commonly, inverse problems are formulated in a static setting where a wealth of theoretical
results and numerical methods are available. The classical theory in Hilbert spaces is found …

The motion of a sample while being scanned in a tomograph prevents its proper volume
reconstruction. In the present study, a procedure is proposed that aims at estimating both the …

Objective. While the spatial and temporal resolution of magnetic particle imaging is very
high, the size of the field of view is limited due to physiological constraints. Multi-patch scans …

Various imaging modalities allow for time-dependent image reconstructions from
measurements where its acquisition also has a time-dependent nature. Magnetic particle …

Advances in learning-based methods are revolutionizing several fields in applied
mathematics, including inverse problems, resulting in a major paradigm shift towards data …

We consider time-dependent inverse problems in a mathematical setting using Lebesgue-
Bochner spaces. Such problems arise when one aims to recover parameters from given …

Imaging modalities have been developed and established as important and powerful tools
to recover characteristics of the interior structure of a studied specimen from induced …

We propose a variational regularization approach based on cylindrical shearlets to deal with
dynamic imaging problems, with dynamic tomography as guiding example. The idea is that …