Independent attenuation correction of whole body [F-18]FDG-PET using a deep learning approach with Generative Adversarial Networks

Armanious, Karim; Hepp, Tobias; Kuestnert, Thomas; Dittmann, Helmut; Nikolaou, Konstantin; La Fougere, Christian; Yang, Bin; Gatidis, Sergios

dc.contributor.author	Armanious, Karim
dc.contributor.author	Hepp, Tobias
dc.contributor.author	Küstner, Thomas
dc.contributor.author	Dittmann, Helmut
dc.contributor.author	Nikolaou, Konstantin
dc.contributor.author	La Fougère, Christian Jean
dc.contributor.author	Gatidis, Sergios
dc.date.accessioned	2020-09-03T14:29:38Z
dc.date.available	2020-09-03T14:29:38Z
dc.date.issued	2020
dc.identifier.issn	2191-219X
dc.identifier.uri	http://hdl.handle.net/10900/106197
dc.language.iso	en	de_DE
dc.publisher	Springer	de_DE
dc.relation.uri	http://dx.doi.org/10.1186/s13550-020-00644-y	de_DE
dc.subject.ddc	610	de_DE
dc.title	Independent attenuation correction of whole body [F-18]FDG-PET using a deep learning approach with Generative Adversarial Networks	de_DE
dc.type	Article	de_DE
utue.quellen.id	20200715072417_00402
utue.personen.roh	Armanious, Karim
utue.personen.roh	Hepp, Tobias
utue.personen.roh	Kuestnert, Thomas
utue.personen.roh	Dittmann, Helmut
utue.personen.roh	Nikolaou, Konstantin
utue.personen.roh	La Fougere, Christian
utue.personen.roh	Yang, Bin
utue.personen.roh	Gatidis, Sergios
dcterms.isPartOf.ZSTitelID	Ejnmmi Research	de_DE
dcterms.isPartOf.ZS-Issue	Article 53	de_DE
dcterms.isPartOf.ZS-Volume	10	de_DE
utue.fakultaet	04 Medizinische Fakultät	de_DE