Hybrid imaging modalities combine two or more medical imaging techniques offering
exciting new possibilities to image the structure, function and biochemistry of the human …

Uncompressed clinical data from modern positron emission tomography (PET) scanners are
very large, exceeding 350 million data points (projection bins). The last decades have seen …

In this paper, we analyze the recently proposed stochastic primal-dual hybrid gradient
(SPDHG) algorithm and provide new theoretical results. In particular, we prove almost sure …

Penalised PET image reconstruction algorithms are often accelerated during early iterations
with the use of subsets. However, these methods may exhibit limit cycle behaviour at later …

Consider the problem of minimizing an expected logarithmic loss over either the probability
simplex or the set of quantum density matrices. This problem includes tasks such as solving …

Iterative reconstruction algorithms are often needed to help solve ill-posed inverse problems
in computed tomography (CT), especially cases when tomographic projection data are …

We consider the problem of minimizing the sum of three convex functions: i) a smooth
function $ f $ in the form of an expectation or a finite average, ii) a non-smooth function $ g …

In this work we propose an efficient stochastic plug-and-play (PnP) algorithm for imaging
inverse problems. The PnP stochastic gradient descent methods have been recently …

The majority of the solvers for the acoustic problem in Photoacoustic Tomography (PAT) rely
on full solution of the wave equation which makes them less suitable for real-time and …

Texture segmentation still constitutes an on-going challenge, especially when processing
large-size images. Recently, procedures integrating a scale-free (or fractal) wavelet-leader …