most citedStochastic Optimisation Framework using the Core Imaging Library and Synergistic Image Reconstruction Framework for PET Reconstruction

1 citations · 1 across the 2 of their papers we have counts for

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2 papers

math.OC2026

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 (…

math.NA2024★ 1 cited

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…