Automated segmentation of endometrial cancer on MR images using deep learning

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 2045-2322

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: 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

Creator: 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

Contributor: SpringerLink (Online service)

DOI: 10.1038/s41598-020-80068-9

URN: urn:nbn:de:101:1-2021020523473605917160

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:32 AM CEST

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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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Automated segmentation of endometrial cancer on MR images using deep learning

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