23 citations · 41 across the 16 of their papers we have counts for
6 papers · 1 filter
3D Uncertainty Quantification for Photoacoustic Tomography
Babak Maboudi Afkham, Amal Mohammed A Alghami, Hassan Yazdanian +1
Photoacoustic tomography (PAT) is a promising modality for high-resolution biomedical imaging, motivating the need for reliable uncertainty quantification (UQ) of reconstructed ima…
Fast reconstruction approaches for photoacoustic tomography with smoothing Sobolev/Matérn priors
Jaakko Kultima, Ronny Ramlau, Teemu Sahlström +1
In photoacoustic tomography (PAT), the computation of the initial pressure distribution within an object from its time-dependent boundary measurements over time is considered. This…
Sparsity promoting reconstructions via hierarchical prior models in diffuse optical tomography
Anssi Manninen, Meghdoot Mozumder, Tanja Tarvainen +1
Diffuse optical tomography (DOT) is a severely ill-posed nonlinear inverse problem that seeks to estimate optical parameters from boundary measurements. In the Bayesian framework,…
On Learned Operator Correction in Inverse Problems
Sebastian Lunz, Andreas Hauptmann, Tanja Tarvainen +2
We discuss the possibility to learn a data-driven explicit model correction for inverse problems and whether such a model correction can be used within a variational framework to o…
The D-bar Method for Diffuse Optical Tomography: a computational study
Janne P. Tamminen, Tanja Tarvainen, Samuli Siltanen
The D-bar method at negative energy is numerically implemented. Using the method we are able to numerically reconstruct potentials and investigate exceptional points at negative en…
Efficient inclusion of total variation type priors in quantitative photoacoustic tomography
Antti Hannukainen, Nuutti Hyvönen, Helle Majander +1
Quantitative photoacoustic tomography is an emerging imaging technique aimed at estimating the distribution of optical parameters inside tissues from photoacoustic images, which ar…