15 citations · 32 across the 24 of their papers we have counts for
6 papers · 1 filter
Plug-and-Play Half-Quadratic Splitting for Ptychography
Alexander Denker, Johannes Hertrich, Zeljko Kereta +3
Ptychography is a coherent diffraction imaging method that uses phase retrieval techniques to reconstruct complex-valued images. It achieves this by sequentially illuminating overl…
Why do we regularise in every iteration for imaging inverse problems?
Evangelos Papoutsellis, Zeljko Kereta, Kostas Papafitsoros
Regularisation is commonly used in iterative methods for solving imaging inverse problems. Many algorithms involve the evaluation of the proximal operator of the regularisation ter…
Data-driven approaches for electrical impedance tomography image segmentation from partial boundary data
Alexander Denker, Zeljko Kereta, Imraj Singh +4
Electrical impedance tomography (EIT) plays a crucial role in non-invasive imaging, with both medical and industrial applications. In this paper, we present three data-driven recon…
Stochastic Optimisation Framework using the Core Imaging Library and Synergistic Image Reconstruction Framework for PET Reconstruction
Evangelos Papoutsellis, Casper da Costa-Luis, Daniel Deidda +10
We introduce a stochastic framework into the open--source Core Imaging Library (CIL) which enables easy development of stochastic algorithms. Five such algorithms from the literatu…
A Guide to Stochastic Optimisation for Large-Scale Inverse Problems
Matthias J. Ehrhardt, Zeljko Kereta, Jingwei Liang +1
Stochastic optimisation algorithms are the de facto standard for machine learning with large amounts of data. Handling only a subset of available data in each optimisation step dra…
Convergence Properties of Score-Based Models for Linear Inverse Problems Using Graduated Optimisation
Pascal Fernsel, Željko Kereta, Alexander Denker
The incorporation of generative models as regularisers within variational formulations for inverse problems has proven effective across numerous image reconstruction tasks. However…