1 citations · 3 across the 4 of their papers we have counts for
4 papers
A Modular Approach to Stochastic Optimisation for Inverse Problems Using the Core Imaging Library
Evangelos Papoutsellis, Margaret A. G. Duff, Jakob S. Jørgensen +5
The Core Imaging Library (CIL) is an open-source versatile Python framework for solving inverse problems with special emphasis on imaging applications such as computed tomography (…
PET Rapid Image Reconstruction Challenge (PETRIC)
Casper da Costa-Luis, Matthias J. Ehrhardt, Christoph Kolbitsch +4
Introduction: We describe the foundation of PETRIC, an image reconstruction challenge to minimise the computational runtime of related algorithms for Positron Emission Tomography (…
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 directional regularization method for the limited-angle Helsinki Tomography Challenge using the Core Imaging Library (CIL)
Jakob Sauer Jørgensen, Evangelos Papoutsellis, Laura Murgatroyd +2
This article presents the algorithms developed by the Core Imaging Library (CIL) developer team for the Helsinki Tomography Challenge 2022. The challenge focused on reconstructing…