75 citations · 132 across the 12 of their papers we have counts for
13 papers
Beyond Independence: on Jointly Normal Priors in Bayesian Inversion
Ruanui Nicholson, Matti Niskanen, Oliver J. Maclaren +1
We consider joint inversion for two or more unknown parameters from observational data in the Bayesian framework. Standard approaches often either treat the parameters as independe…
Approximation error method for imaging the human head by electrical impedance tomography
Valentina Candiani, Nuutti Hyvönen, Jari P. Kaipio +1
This work considers electrical impedance tomography imaging of the human head, with the ultimate goal of locating and classifying a stroke in emergency care. One of the main diffic…
Model reduction in acoustic inversion by artificial neural network
Janne Koponen, Timo Lähivaara, Jari Kaipio +1
In ultrasound tomography, the speed of sound inside an object is estimated based on acoustic measurements carried out by sensors surrounding the object. An accurate forward model i…
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…
Estimating the material parameters of an inhomogeneous poroelastic plate from ultrasonic measurements in water
Matti Niskanen, Aroune Duclos, Olivier Dazel +3
The estimation of poroelastic material parameters based on ultrasound measurements is considered. The acoustical characterisation of poroelastic materials based on various measurem…
A Bayesian approach to improving the Born approximation for inverse scattering with high contrast materials
Jari P. Kaipio, Tomi Huttunen, Teemu Luostari +2
Time harmonic inverse scattering using accurate forward models is often computationally expensive. On the other hand, the use of computationally efficient solvers, such as the Born…
An Additive Approximation to Multiplicative Noise
Ruanui Nicholson, Jari P. Kaipio
Multiplicative noise models are often used instead of additive noise models in cases in which the noise variance depends on the state. Furthermore, when Poisson distributions with…
Estimation of the Robin coefficient field in a Poisson problem with uncertain conductivity field
Ruanui Nicholson, Noemi Petra, Jari Kaipio
We consider the reconstruction of a heterogeneous coefficient field in a Robin boundary condition on an inaccessible part of the boundary in a Poisson problem with an uncertain (or…
Prior Variances and Depth Un-Biased Estimators in EEG Focal Source Imaging
Alexandra Koulouri, Ville Rimpiläinen, Mike Brookes +1
In electroencephalography (EEG) source imaging, the inverse source estimates are depth biased in such a way that their maxima are often close to the sensors. This depth bias can be…
Bayesian Modelling of Skull Conductivity Uncertainties in EEG Source Imaging
Ville Rimpiläinen, Alexandra Koulouri, Felix Lucka +2
Knowing the correct skull conductivity is crucial for the accuracy of EEG source imaging, but unfortunately, its true value, which is inter- and intra-individually varying, is diff…
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…
Reduced-order model for electrical impedance tomography based on proper orthogonal decomposition
Antti Lipponen, Aku Seppänen, Jari Kaipio
Electrical impedance tomography (EIT) is an imaging modality in which the conductivity distribution inside a target is reconstructed based on voltage measurements from the surface…
Generalized Optimal Current Patterns and Electrical Safety in EIT
William R. B. Lionheart, Jari Kaipio, Christopher N. McLeod
There are a number of constraints which limit the current and voltages which can be applied on a multiple drive electrical imaging system. One obvious constraint is to limit the ma…