Editorial: generative adversarial networks in cardiovascular research

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buir.contributor.authorÇukur, Tolga
buir.contributor.orcidÇukur, Tolga|0000-0002-2296-851X
dc.citation.epage1307812-3en_US
dc.citation.spage1307812-1
dc.citation.volumeNumber10
dc.contributor.authorZhang, Q.
dc.contributor.authorÇukur, Tolga
dc.contributor.authorGreenspan, H.
dc.contributor.authorYang, G.
dc.date.accessioned2024-03-13T13:22:27Z
dc.date.available2024-03-13T13:22:27Z
dc.date.issued2023-10-23
dc.departmentNational Magnetic Resonance Research Center (UMRAM)
dc.departmentDepartment of Electrical and Electronics Engineering
dc.description.provenanceMade available in DSpace on 2024-03-13T13:22:27Z (GMT). No. of bitstreams: 1 Editorial_generative_adversarial_networks_in_cardiovascular_research.pdf: 146961 bytes, checksum: 19a39b7cd5e9666bb8bdb002500648e7 (MD5) Previous issue date: 2023-10-23en
dc.identifier.doi10.3389/fcvm.2023.1307812
dc.identifier.eissn2297-055X
dc.identifier.urihttps://hdl.handle.net/11693/114699
dc.language.isoEnglish
dc.publisherFrontiers Research Foundation
dc.relation.isversionofhttps://dx.doi.org/10.3389/fcvm.2023.1307812
dc.source.titleFrontiers in Cardiovascular Medicine
dc.subjectDeep generative models
dc.subjectGenerative adversarial networks (GAN)
dc.subjectEchocardiography (Echo)
dc.subjectCardiovascular magnetic resonance
dc.subjectSegmentation (Image processing)
dc.titleEditorial: generative adversarial networks in cardiovascular research
dc.typeEditorial

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