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http://hdl.handle.net/2445/174752
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DC Field | Value | Language |
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dc.contributor.author | Raisi-Estabragh, Zahra | - |
dc.contributor.author | Izquierdo, Cristian | - |
dc.contributor.author | Campello Román, Víctor Manuel | - |
dc.contributor.author | Martin Isla, Carlos | - |
dc.contributor.author | Jaggi, Akshay | - |
dc.contributor.author | Harvey, Nicholas C. | - |
dc.contributor.author | Lekadir, Karim, 1977- | - |
dc.contributor.author | Petersen, Steffen E. | - |
dc.date.accessioned | 2021-03-09T09:39:46Z | - |
dc.date.available | 2021-03-09T09:39:46Z | - |
dc.date.issued | 2020-03-06 | - |
dc.identifier.issn | 2047-2404 | - |
dc.identifier.uri | http://hdl.handle.net/2445/174752 | - |
dc.description.abstract | Radiomics is a novel image analysis technique, whereby voxel-level information is extracted from digital images and used to derive multiple numerical quantifiers of shape and tissue character. Cardiac magnetic resonance (CMR) is the reference imaging modality for assessment of cardiac structure and function. Conventional analysis of CMR scans is mostly reliant on qualitative image analysis and basic geometric quantifiers. Small proof-of-concept studies have demonstrated the feasibility and superior diagnostic accuracy of CMR radiomics analysis over conventional reporting. CMR radiomics has the potential to transform our approach to defining image phenotypes and, through this, improve diagnostic accuracy, treatment selection, and prognostication. The purpose of this article is to provide an overview of radiomics concepts for clinicians, with particular consideration of application to CMR. We will also review existing literature on CMR radiomics, discuss challenges, and consider directions for future work. | - |
dc.format.extent | 8 p. | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | - |
dc.publisher | Oxford University Press | - |
dc.relation.isformatof | Reproducció del document publicat a: https://doi.org/10.1093/ehjci/jeaa028 | - |
dc.relation.ispartof | European Heart Journal-Cardiovascular Imaging, 2020, vol. 21, num. 4, p. 349-356 | - |
dc.relation.uri | https://doi.org/10.1093/ehjci/jeaa028 | - |
dc.rights | (c) cc-by Raisi Estabragh, Zahra et al., 2020 | - |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.source | Articles publicats en revistes (Matemàtiques i Informàtica) | - |
dc.subject.classification | Ressonància magnètica | - |
dc.subject.classification | Diagnòstic per la imatge | - |
dc.subject.classification | Aprenentatge automàtic | - |
dc.subject.other | Magnetic resonance | - |
dc.subject.other | Diagnostic imaging | - |
dc.subject.other | Machine learning | - |
dc.title | Cardiac magnetic resonance radiomics: basic principles and clinical perspectives | - |
dc.type | info:eu-repo/semantics/article | - |
dc.type | info:eu-repo/semantics/acceptedVersion | - |
dc.type | info:eu-repo/semantics/publishedVersion | - |
dc.identifier.idgrec | 705782 | - |
dc.date.updated | 2021-03-09T09:39:46Z | - |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/825903/EU//euCanSHare | - |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
dc.identifier.pmid | 32142107 | - |
Appears in Collections: | Articles publicats en revistes (Matemàtiques i Informàtica) Publicacions de projectes de recerca finançats per la UE |
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705782.pdf | 504.81 kB | Adobe PDF | View/Open |
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