Diagnostic Confidence and Feasibility of a Deep Learning Accelerated HASTE Sequence of the Abdomen in a Single Breath-Hold

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dc.contributor.author Herrmann, Judith
dc.contributor.author Gassenmaier, Sebastian
dc.contributor.author Afat, Saif
dc.contributor.author Lingg, Andreas
dc.contributor.author Kundel, Matthias
dc.contributor.author Othman, Ahmed
dc.date.accessioned 2021-12-27T09:21:00Z
dc.date.available 2021-12-27T09:21:00Z
dc.date.issued 2021
dc.identifier.issn 1536-0210
dc.identifier.uri http://hdl.handle.net/10900/122162
dc.language.iso en de_DE
dc.publisher Lippincott Williams & Wilkins de_DE
dc.relation.uri http://dx.doi.org/10.1097/RLI.0000000000000743 de_DE
dc.subject.ddc 610 de_DE
dc.title Diagnostic Confidence and Feasibility of a Deep Learning Accelerated HASTE Sequence of the Abdomen in a Single Breath-Hold de_DE
dc.type Article de_DE
utue.quellen.id 20210824232002_01432
utue.publikation.seiten 313-319 de_DE
utue.personen.roh Herrmann, Judith
utue.personen.roh Gassenmaier, Sebastian
utue.personen.roh Nickel, Dominik
utue.personen.roh Arberet, Simon
utue.personen.roh Afat, Saif
utue.personen.roh Lingg, Andreas
utue.personen.roh Kundel, Matthias
utue.personen.roh Othman, Ahmed E.
dcterms.isPartOf.ZSTitelID Investigative Radiology de_DE
dcterms.isPartOf.ZS-Issue 5 de_DE
dcterms.isPartOf.ZS-Volume 56 de_DE
utue.fakultaet 04 Medizinische Fakultät de_DE


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