Staging and quantification of florbetaben PET images using machine learning: impact of predicted regional cortical tracer uptake and amyloid stage on clinical outcomes

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1619-7089

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Staging and quantification of florbetaben PET images using machine learning: impact of predicted regional cortical tracer uptake and amyloid stage on clinical outcomes ; volume:47 ; number:8 ; day:28 ; month:12 ; year:2019 ; pages:1971-1983 ; date:7.2020
European journal of nuclear medicine and molecular imaging ; 47, Heft 8 (28.12.2019), 1971-1983, 7.2020

Creator: Kim, Jun Pyo
Kim, Jeonghun
Kim, Yeshin
Moon, Seung Hwan
Park, Yu Hyun
Yoo, Sole
Jang, Hyemin
Kim, Hee Jin
Na, Duk L.
Seo, Sang Won
Seong, Joon-Kyung

Contributor: SpringerLink (Online service)

DOI: 10.1007/s00259-019-04663-3

URN: urn:nbn:de:101:1-2020092715232165897393

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

Last update: 14.08.2025, 11:01 AM CEST

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Associated

Kim, Jun Pyo
Kim, Jeonghun
Kim, Yeshin
Moon, Seung Hwan
Park, Yu Hyun
Yoo, Sole
Jang, Hyemin
Kim, Hee Jin
Na, Duk L.
Seo, Sang Won
Seong, Joon-Kyung
SpringerLink (Online service)

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Staging and quantification of florbetaben PET images using machine learning: impact of predicted regional cortical tracer uptake and amyloid stage on clinical outcomes

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