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Simulated late gadolinium enhanced cardiac magnetic resonance imaging dataset from mechanical XCAT phantom including a myocardial infarct

The late enhanced magnetic resonance image dataset in this article is simulated using a mechanistic cardiac phantom that includes an myocardial infarct. Settings of the image simulation pipeline are adjusted such that high- and low-resolution images, with and without slice alignment artifacts, are s...

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Detalles Bibliográficos
Autores principales: Kruithof, Evianne, Amirrajab, Sina, Lau, Kevin D., Breeuwer, Marcel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8693344/
https://www.ncbi.nlm.nih.gov/pubmed/34984215
http://dx.doi.org/10.1016/j.dib.2021.107691
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author Kruithof, Evianne
Amirrajab, Sina
Lau, Kevin D.
Breeuwer, Marcel
author_facet Kruithof, Evianne
Amirrajab, Sina
Lau, Kevin D.
Breeuwer, Marcel
author_sort Kruithof, Evianne
collection PubMed
description The late enhanced magnetic resonance image dataset in this article is simulated using a mechanistic cardiac phantom that includes an myocardial infarct. Settings of the image simulation pipeline are adjusted such that high- and low-resolution images, with and without slice alignment artifacts, are simulated. Our article on the influence of image artifacts on image-based models of the cardiac electrophysiology is based on this data (Kruithof et al., 2021). This dataset provides image-analysis researchers a reference to perform validation of their methods using the included high-resolution ground truth image, a resource that is often unavailable clinically.
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spelling pubmed-86933442022-01-03 Simulated late gadolinium enhanced cardiac magnetic resonance imaging dataset from mechanical XCAT phantom including a myocardial infarct Kruithof, Evianne Amirrajab, Sina Lau, Kevin D. Breeuwer, Marcel Data Brief Data Article The late enhanced magnetic resonance image dataset in this article is simulated using a mechanistic cardiac phantom that includes an myocardial infarct. Settings of the image simulation pipeline are adjusted such that high- and low-resolution images, with and without slice alignment artifacts, are simulated. Our article on the influence of image artifacts on image-based models of the cardiac electrophysiology is based on this data (Kruithof et al., 2021). This dataset provides image-analysis researchers a reference to perform validation of their methods using the included high-resolution ground truth image, a resource that is often unavailable clinically. Elsevier 2021-12-08 /pmc/articles/PMC8693344/ /pubmed/34984215 http://dx.doi.org/10.1016/j.dib.2021.107691 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data Article
Kruithof, Evianne
Amirrajab, Sina
Lau, Kevin D.
Breeuwer, Marcel
Simulated late gadolinium enhanced cardiac magnetic resonance imaging dataset from mechanical XCAT phantom including a myocardial infarct
title Simulated late gadolinium enhanced cardiac magnetic resonance imaging dataset from mechanical XCAT phantom including a myocardial infarct
title_full Simulated late gadolinium enhanced cardiac magnetic resonance imaging dataset from mechanical XCAT phantom including a myocardial infarct
title_fullStr Simulated late gadolinium enhanced cardiac magnetic resonance imaging dataset from mechanical XCAT phantom including a myocardial infarct
title_full_unstemmed Simulated late gadolinium enhanced cardiac magnetic resonance imaging dataset from mechanical XCAT phantom including a myocardial infarct
title_short Simulated late gadolinium enhanced cardiac magnetic resonance imaging dataset from mechanical XCAT phantom including a myocardial infarct
title_sort simulated late gadolinium enhanced cardiac magnetic resonance imaging dataset from mechanical xcat phantom including a myocardial infarct
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8693344/
https://www.ncbi.nlm.nih.gov/pubmed/34984215
http://dx.doi.org/10.1016/j.dib.2021.107691
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