End-to-End Deep Learning of Non-rigid Groupwise Registration and Reconstruction of Dynamic MRI

dc.contributor.author	Küstner, Thomas
dc.date.accessioned	2023-11-17T10:00:45Z
dc.date.available	2023-11-17T10:00:45Z
dc.date.issued	2022
dc.identifier.issn	2297-055X
dc.identifier.uri	http://hdl.handle.net/10900/147840
dc.language.iso	en	en
dc.publisher	Lausanne : Frontiers Media Sa	de_DE
dc.relation.uri	http://dx.doi.org/10.3389/fcvm.2022.880186
dc.subject.ddc	610	de_DE
dc.title	End-to-End Deep Learning of Non-rigid Groupwise Registration and Reconstruction of Dynamic MRI	de_DE
dc.type	Article	de_DE
utue.quellen.id	20230925000000_03945
utue.personen.roh	Yang, Junwei
utue.personen.roh	Kuestner, Thomas
utue.personen.roh	Hu, Peng
utue.personen.roh	Lio, Pietro
utue.personen.roh	Qi, Haikun
dcterms.isPartOf.ZSTitelID	Frontiers in Cardiovascular Medicine	de_DE
dcterms.isPartOf.ZS-Issue	Article 880186	de_DE
dcterms.isPartOf.ZS-Volume	9	de_DE
utue.fakultaet	04 Medizinische Fakultät

Files in this item

Files	Size	Format	View
There are no files associated with this item.