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Synergistic tomographic image reconstruction: part 1

Tsoumpas, C; Jørgensen, JS; Kolbitsch, C; Thielemans, K; (2021) Synergistic tomographic image reconstruction: part 1. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences , 379 (2200) , Article 20200189. 10.1098/rsta.2020.0189. Green open access

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Abstract

This special issue focuses on synergistic tomographic image reconstruction in a range of contributions in multiple disciplines and various application areas. The topic of image reconstruction covers substantial inverse problems (Mathematics) which are tackled with various methods including statistical approaches (e.g. Bayesian methods, Monte Carlo) and computational approaches (e.g. machine learning, computational modelling, simulations). The issue is separated in two volumes. This volume focuses mainly on algorithms and methods. Some of the articles will demonstrate their utility on real-world challenges, either medical applications (e.g. cardiovascular diseases, proton therapy planning) or applications in material sciences (e.g. material decomposition and characterization). One of the desired outcomes of the special issue is to bring together different scientific communities which do not usually interact as they do not share the same platforms (such as journals and conferences). This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.

Type: Article
Title: Synergistic tomographic image reconstruction: part 1
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1098/rsta.2020.0189
Publisher version: http://dx.doi.org/10.1098/rsta.2020.0189
Language: English
Additional information: © 2021 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
Keywords: computed tomography, electrical impedance tomography, imaging, magnetic resonance imaging, positron emission tomography, tomography
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Department of Imaging
URI: https://discovery.ucl.ac.uk/id/eprint/10128108
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