23 citations · 41 across the 16 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…
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…
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…