We propose a new algorithmic approach to the non-smooth and non-convex Potts problem
(also called piecewise-constant Mumford–Shah problem) for inverse imaging problems. We …

In this paper we study the reconstruction of moving object densities from undersampled
dynamic x-ray tomography in two dimensions. A particular motivation of this study is to use …

Reaching the full potential of X-ray nanotomography, in particular for biological samples, is
limited by many factors, of which one of the most serious is radiation damage. Although …

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 …

An inverse problem is called dynamic if the object changes during the data acquisition
process. This occurs eg in medical applications when fast moving organs like the lungs or …

Motion, eg, due to patient movement or improper device calibration, is inevitable in many
imaging modalities such as photoacoustic tomography (PAT) by a rotating system and can …

In this paper we propose a motion-aware variational approach to reconstruct moving objects
from sparse dynamic data. The motivation of this work stems from x-ray imaging of plants …

In this paper, we propose a prior-based dimension reduction Kalman filter for undersampled
dynamic X-ray tomography. With this method, the X-ray reconstructions are parameterized …

A novel variant of the level set method is introduced for dynamic X-ray tomography. The
target is allowed to change in time while being imaged by one or several source–detector …