This paper surveys variational approaches for image reconstruction in dynamic inverse
problems. Emphasis is on variational methods that rely on parametrized temporal models …

The inverse problem in electro-and magneto-encephalography (EEG/MEG) aims at
reconstructing the underlying current distribution in the human brain using potential …

We present a new approach for estimating solutions of the dynamical inverse problem of
EEG generation. In contrast to previous approaches, we reinterpret this problem as a filtering …

Electrical capacitance tomography (ECT) is a relatively mature non-invasive imaging
technique that attempts to map dielectric permittivity of materials. ECT has become a …

The estimation of the activity-related ion currents by measuring the induced electromagnetic
fields at the head surface is a challenging and severely ill-posed inverse problem. This is …

We develop a dynamic generalized conditional gradient method (DGCG) for dynamic
inverse problems with optimal transport regularization. We consider the framework …

Time plays an important role in medical and neuropsychological diagnosis and research. In
the field of Electro-and MagnetoEncephaloGraphy (EEG/MEG) source localization, a current …

We apply state space estimation techniques to the time-varying reconstruction problem in
optical tomography. We develop a stochastic model for describing the evolution of quasi …

This paper presents a new algorithm called Standardized Shrinking LORETA-FOCUSS
(SSLOFO) for solving the electroencephalogram (EEG) inverse problem. Multiple techniques …

A crucial limitation of current high-resolution 3D photoacoustic tomography (PAT) devices
that employ sequential scanning is their long acquisition time. In previous work, we …