Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/174752
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dc.contributor.authorRaisi-Estabragh, Zahra-
dc.contributor.authorIzquierdo, Cristian-
dc.contributor.authorCampello Román, Víctor Manuel-
dc.contributor.authorMartin Isla, Carlos-
dc.contributor.authorJaggi, Akshay-
dc.contributor.authorHarvey, Nicholas C.-
dc.contributor.authorLekadir, Karim, 1977--
dc.contributor.authorPetersen, Steffen E.-
dc.date.accessioned2021-03-09T09:39:46Z-
dc.date.available2021-03-09T09:39:46Z-
dc.date.issued2020-03-06-
dc.identifier.issn2047-2404-
dc.identifier.urihttp://hdl.handle.net/2445/174752-
dc.description.abstractRadiomics 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.extent8 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherOxford University Press-
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1093/ehjci/jeaa028-
dc.relation.ispartofEuropean Heart Journal-Cardiovascular Imaging, 2020, vol. 21, num. 4, p. 349-356-
dc.relation.urihttps://doi.org/10.1093/ehjci/jeaa028-
dc.rights(c) cc-by Raisi Estabragh, Zahra et al., 2020-
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.sourceArticles publicats en revistes (Matemàtiques i Informàtica)-
dc.subject.classificationRessonància magnètica-
dc.subject.classificationDiagnòstic per la imatge-
dc.subject.classificationAprenentatge automàtic-
dc.subject.otherMagnetic resonance-
dc.subject.otherDiagnostic imaging-
dc.subject.otherMachine learning-
dc.titleCardiac magnetic resonance radiomics: basic principles and clinical perspectives-
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/acceptedVersion-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.identifier.idgrec705782-
dc.date.updated2021-03-09T09:39:46Z-
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/825903/EU//euCanSHare-
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
dc.identifier.pmid32142107-
Appears in Collections:Articles publicats en revistes (Matemàtiques i Informàtica)
Publicacions de projectes de recerca finançats per la UE

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