Deep-learning-based pelvic automatic segmentation in pelvic fractures

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Standort: Deutsche Nationalbibliothek Frankfurt am Main

Umfang: 1 Online-Ressource.

Sprache: Englisch

Erschienen in: Deep-learning-based pelvic automatic segmentation in pelvic fractures ; volume:14 ; number:1 ; day:28 ; month:5 ; year:2024 ; pages:1-8 ; date:12.2024
Scientific reports ; 14, Heft 1 (28.5.2024), 1-8, 12.2024

Urheber: Lee, Jung Min
Park, Jun Young
Kim, Young Jae
Kim, Kwang Gi

Beteiligte Personen und Organisationen: SpringerLink (Online service)

DOI: 10.1038/s41598-024-63093-w

URN: urn:nbn:de:101:1-2408061001216.953971996616

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

Letzte Aktualisierung: 14.08.2025, 11:00 MESZ

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Beteiligte

Lee, Jung Min
Park, Jun Young
Kim, Young Jae
Kim, Kwang Gi
SpringerLink (Online service)

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Deep-learning-based pelvic automatic segmentation in pelvic fractures

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Ähnliche Objekte (12)

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