23 citations · 41 across the 16 of their papers we have counts for
17 papers
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…
Utilising a learned forward operator in the inverse problem of photoacoustic tomography
Karoliina Puronhaara, Teemu Sahlström, Andreas Hauptmann +1
We study the use of a learned forward operator in the inverse problem of photoacoustic tomography. The Fourier neural operator to approximate the photoacoustic wave propagation is…
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…
Reconstructing initial pressure and speed of sound distributions simultaneously in photoacoustic tomography
Miika Suhonen, Felix Lucka, Aki Pulkkinen +3
Image reconstruction in photoacoustic tomography relies on an accurate knowledge of the speed of sound in the target. However, the speed of sound distribution is not generally know…
Simultaneous estimation of electrical conductivity and permittivity in quantitative thermoacoustic tomography
Teemu Sahlström, Timo Lähivaara, Tanja Tarvainen
In this work, the inverse problem of quantitative thermoacoustic tomography is studied. In quantitative thermoacoustic tomography, dielectric parameters of an imaged target are est…
Model-based reconstructions for quantitative imaging in photoacoustic tomography
Andreas Hauptmann, Tanja Tarvainen
The reconstruction task in photoacoustic tomography can vary a lot depending on measured targets, geometry, and especially the quantity we want to recover. Specifically, as the sig…
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…
Utilising nanosecond sources in diffuse optical tomography
Meghdoot Mozumder, Jarkko Leskinen, Tanja Tarvainen
Diffuse optical tomography (DOT) use near-infrared light for imaging optical properties of biological tissues. Time-domain DOT systems use pulsed lasers and measure time-varying te…
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,…
Utilizing variational autoencoders in the Bayesian inverse problem of photoacoustic tomography
Teemu Sahlström, Tanja Tarvainen
There has been an increasing interest in utilizing machine learning methods in inverse problems and imaging. Most of the work has, however, concentrated on image reconstruction pro…
A model-based iterative learning approach for diffuse optical tomography
Meghdoot Mozumder, Andreas Hauptmann, Ilkka Nissilä +2
Diffuse optical tomography (DOT) utilises near-infrared light for imaging spatially distributed optical parameters, typically the absorption and scattering coefficients. The image…
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…
Coupled Elastic-Acoustic Modelling for Quantitative Photoacoustic Tomography
Hwan Goh, Timo Lahivaara, Tanja Tarvainen +4
Quantitative photoacoustic tomography (qPAT) is an imaging technique aimed at estimating chromophore concentrations inside tissues from photoacoustic images, which are formed by co…
Perturbation Monte Carlo Method for Quantitative Photoacoustic Tomography
Aleksi Leino, Tuomas Lunttila, Meghdoot Mozumder +2
Quantitative photoacoustic tomography aims at estimating optical parameters from photoacoustic images that are formed utilizing the photoacoustic effect caused by the absorption of…
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…
Approximate Marginalization of Absorption and Scattering in Fluorescence Diffuse Optical Tomography
Meghdoot Mozumder, Tanja Tarvainen, Simon Arridge +3
In fluorescence diffuse optical tomography (fDOT), the reconstruction of the fluorophore concentration inside the target body is usually carried out using a normalized Born approxi…