AI Lung Segmentation and Perfusion Analysis of Dual-Energy CT Can Help to Distinguish COVID-19 Infiltrates from Visually Similar Immunotherapy-Related Pneumonitis Findings and Can Optimize Radiological Workflows

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dc.contributor.author Mader, Markus
dc.contributor.author Gassenmaier, Sebastian
dc.contributor.author Nikolaou, Konstantin
dc.contributor.author Afat, Saif
dc.contributor.author Brendlin, Andreas Stefan
dc.contributor.author Othman, Ahmed
dc.date.accessioned 2023-04-24T06:42:44Z
dc.date.available 2023-04-24T06:42:44Z
dc.date.issued 2022
dc.identifier.issn 2379-1381
dc.identifier.uri http://hdl.handle.net/10900/139500
dc.language.iso en de_DE
dc.publisher Mdpi de_DE
dc.relation.uri http://dx.doi.org/10.3390/tomography8010003 de_DE
dc.subject.ddc 610 de_DE
dc.title AI Lung Segmentation and Perfusion Analysis of Dual-Energy CT Can Help to Distinguish COVID-19 Infiltrates from Visually Similar Immunotherapy-Related Pneumonitis Findings and Can Optimize Radiological Workflows de_DE
dc.type Article de_DE
utue.quellen.id 20220728000000_02133
utue.publikation.seiten 22-32 de_DE
utue.personen.roh Brendlin, Andreas S.
utue.personen.roh Mader, Markus
utue.personen.roh Faby, Sebastian
utue.personen.roh Schmidt, Bernhard
utue.personen.roh Othman, Ahmed E.
utue.personen.roh Gassenmaier, Sebastian
utue.personen.roh Nikolaou, Konstantin
utue.personen.roh Afat, Saif
dcterms.isPartOf.ZSTitelID Tomography de_DE
dcterms.isPartOf.ZS-Issue 1 de_DE
dcterms.isPartOf.ZS-Volume 8 de_DE
utue.fakultaet 04 Medizinische Fakultät de_DE


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