Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging

Manini, Chiara; Huellebrand, Markus; Walczak, Lars; Nordmeyer, Sarah; Jarmatz, Lina; Kuehne, Titus; Stern, Heiko; Meierhofer, Christian; Harloff, Andreas; Erley, Jennifer; Bannas, Peter; Kelle, Sebastian; Trauzeddel, Ralf Felix; Schulz-Menger, Jeanette; Hennemuth, Anja

dc.contributor.author	Nordmeyer, Sarah
dc.date.accessioned	2025-06-16T06:34:48Z
dc.date.available	2025-06-16T06:34:48Z
dc.date.issued	2024
dc.identifier.issn	1097-6647
dc.identifier.uri	http://hdl.handle.net/10900/166679
dc.language.iso	en	de_DE
dc.publisher	New York : Elsevier Science Inc	de_DE
dc.relation.uri	http://dx.doi.org/10.1016/j.jocmr.2024.101081	de_DE
dc.subject.ddc	610	de_DE
dc.title	Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging	de_DE
dc.type	Article	de_DE
utue.quellen.id	20250203000000_01299
utue.personen.roh	Manini, Chiara
utue.personen.roh	Huellebrand, Markus
utue.personen.roh	Walczak, Lars
utue.personen.roh	Nordmeyer, Sarah
utue.personen.roh	Jarmatz, Lina
utue.personen.roh	Kuehne, Titus
utue.personen.roh	Stern, Heiko
utue.personen.roh	Meierhofer, Christian
utue.personen.roh	Harloff, Andreas
utue.personen.roh	Erley, Jennifer
utue.personen.roh	Bannas, Peter
utue.personen.roh	Kelle, Sebastian
utue.personen.roh	Trauzeddel, Ralf Felix
utue.personen.roh	Schulz-Menger, Jeanette
utue.personen.roh	Hennemuth, Anja
dcterms.isPartOf.ZSTitelID	Journal of Cardiovascular Magnetic Resonance	de_DE
dcterms.isPartOf.ZS-Issue	Article 101081	de_DE
dcterms.isPartOf.ZS-Volume	26 (2)	de_DE
utue.fakultaet	04 Medizinische Fakultät	de_DE