Deep Learning-Based Superresolution Reconstruction for Upper Abdominal Magnetic Resonance Imaging An Analysis of Image Quality, Diagnostic Confidence, and Lesion Conspicuity

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dc.contributor.author Al Mansour, Haidara
dc.contributor.author Gassenmaier, Sebastian
dc.contributor.author Afat, Saif
dc.contributor.author Hoffmann, Rüdiger
dc.contributor.author Othman, Ahmed
dc.date.accessioned 2021-10-28T12:38:59Z
dc.date.available 2021-10-28T12:38:59Z
dc.date.issued 2021
dc.identifier.issn 1536-0210
dc.identifier.uri http://hdl.handle.net/10900/120214
dc.language.iso en de_DE
dc.publisher Lippincott Williams & Wilkins de_DE
dc.relation.uri http://dx.doi.org/10.1097/RLI.0000000000000769 de_DE
dc.subject.ddc 610 de_DE
dc.title Deep Learning-Based Superresolution Reconstruction for Upper Abdominal Magnetic Resonance Imaging An Analysis of Image Quality, Diagnostic Confidence, and Lesion Conspicuity de_DE
dc.type Article de_DE
utue.quellen.id 20210824232002_00138
utue.publikation.seiten 509-516 de_DE
utue.personen.roh Almansour, Haidara
utue.personen.roh Gassenmaier, Sebastian
utue.personen.roh Nickel, Dominik
utue.personen.roh Kannengiesser, Stephan
utue.personen.roh Afat, Saif
utue.personen.roh Weiss, Jakob
utue.personen.roh Hoffmann, Rudiger
utue.personen.roh Othman, Ahmed E.
dcterms.isPartOf.ZSTitelID Investigative Radiology de_DE
dcterms.isPartOf.ZS-Issue 8 de_DE
dcterms.isPartOf.ZS-Volume 56 de_DE
utue.fakultaet 04 Medizinische Fakultät de_DE


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