26 citations · 146 across the 20 of their papers we have counts for
20 papers
Deep Learning Based Reconstruction Methods for Electrical Impedance Tomography
Alexander Denker, Fabio Margotti, Jianfeng Ning +5
Electrical Impedance Tomography (EIT) is a powerful imaging modality widely used in medical diagnostics, industrial monitoring, and environmental studies. The EIT inverse problem i…
Fictitious null spaces for improving the solution of injective inverse problems
Ole Løseth Elvetun, Kim Knudsen, Bjørn Fredrik Nielsen
For linear ill-posed problems with nontrivial null spaces, Tikhonov regularization and truncated singular value decomposition (TSVD) typically yield solutions that are close to the…
A Bayesian approach for consistent reconstruction of inclusions
Babak Maboudi Afkham, Kim Knudsen, Aksel Kaastrup Rasmussen +1
This paper considers a Bayesian approach for inclusion detection in nonlinear inverse problems using two known and popular push-forward prior distributions: the star-shaped and lev…
Conductivity reconstruction from power density data in limited view
Bjørn Jensen, Kim Knudsen, Hjørdis Schlüter
In Acousto-Electric tomography, the objective is to extract information about the interior electrical conductivity in a physical body from knowledge of the interior power density d…
Reconstructing anisotropic conductivities on two-dimensional Riemannian manifolds from power densities
Kim Knudsen, Steen Markvorsen, Hjørdis Schlüter
We consider an electrically conductive compact two-dimensional Riemannian manifold with smooth boundary. This setting defines a natural conductive Laplacian on the manifold and hen…
Direct regularized reconstruction for the three-dimensional Calderón problem
Kim Knudsen, Aksel K. Rasmussen
Electrical Impedance Tomography gives rise to the severely ill-posed Calderón problem of determining the electrical conductivity distribution in a bounded domain from knowledge of…