Automated segmentation of endometrial cancer on MR images using deep learning
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
2045-2322
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
Automated segmentation of endometrial cancer on MR images using deep learning ; volume:11 ; number:1 ; day:8 ; month:1 ; year:2021 ; pages:1-8 ; date:12.2021
Scientific reports ; 11, Heft 1 (8.1.2021), 1-8, 12.2021
- Urheber
-
Hodneland, Erlend
Dybvik, Julie A.
Wagner-Larsen, Kari S.
Šoltészová, Veronika
Munthe-Kaas, Antonella Z.
Fasmer, Kristine E.
Krakstad, Camilla
Lundervold, Arvid
Lundervold, Alexander S.
Salvesen, Øyvind
Erickson, Bradley J.
Haldorsen, Ingfrid
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1038/s41598-020-80068-9
- URN
-
urn:nbn:de:101:1-2021020523473605917160
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:32 MESZ
Datenpartner
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Beteiligte
- Hodneland, Erlend
- Dybvik, Julie A.
- Wagner-Larsen, Kari S.
- Šoltészová, Veronika
- Munthe-Kaas, Antonella Z.
- Fasmer, Kristine E.
- Krakstad, Camilla
- Lundervold, Arvid
- Lundervold, Alexander S.
- Salvesen, Øyvind
- Erickson, Bradley J.
- Haldorsen, Ingfrid
- SpringerLink (Online service)
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