Exploring the utility of radiomic feature extraction to improve the diagnostic accuracy of cardiac sarcoidosis using FDG PET

Mushari, NA, Soultanidis, G, Duff, L et al. (4 more authors) (2022) Exploring the utility of radiomic feature extraction to improve the diagnostic accuracy of cardiac sarcoidosis using FDG PET. Frontiers in Medicine, 9. 840261. ISSN 2296-858X

Abstract

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Authors/Creators:
  • Mushari, NA
  • Soultanidis, G
  • Duff, L
  • Trivieri, MG
  • Fayad, ZA
  • Robson, P
  • Tsoumpas, C
Copyright, Publisher and Additional Information: © 2022 Mushari, Soultanidis, Duff, Trivieri, Fayad, Robson and Tsoumpas. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Keywords: cardiac sarcoidosis, PET-MRI, imaging, radiomics, machine learning
Dates:
  • Accepted: 1 February 2022
  • Published: 28 February 2022
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds)
The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 23 Feb 2022 11:20
Last Modified: 11 Mar 2022 15:02
Status: Published
Publisher: Frontiers Media
Identification Number: https://doi.org/10.3389/fmed.2022.840261

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