Controls-based denoising, a new approach for medical image analysis, improves prediction of conversion to Alzheimer's disease with FDG-PET

Blum, Dominik; Liepelt-Scarfone, Inga; Berg, Daniela; Gasser, Thomas; la Fougere, Christian; Reimold, Matthias

dc.contributor.author	Blum, Dominik
dc.contributor.author	Liepelt, Inga
dc.contributor.author	Gasser, Thomas
dc.contributor.author	Reimold, Matthias
dc.contributor.author	La Fougère, Christian Jean
dc.date.accessioned	2020-05-07T13:03:35Z
dc.date.available	2020-05-07T13:03:35Z
dc.date.issued	2019
dc.identifier.issn	1619-7089
dc.identifier.uri	http://hdl.handle.net/10900/100338
dc.language.iso	en	de_DE
dc.publisher	Springer	de_DE
dc.relation.uri	http://dx.doi.org/10.1007/s00259-019-04400-w	de_DE
dc.subject.ddc	610	de_DE
dc.title	Controls-based denoising, a new approach for medical image analysis, improves prediction of conversion to Alzheimer's disease with FDG-PET	de_DE
dc.type	Article	de_DE
utue.quellen.id	20190926111821_00021
utue.publikation.seiten	2370-2379	de_DE
utue.personen.roh	Blum, Dominik
utue.personen.roh	Liepelt-Scarfone, Inga
utue.personen.roh	Berg, Daniela
utue.personen.roh	Gasser, Thomas
utue.personen.roh	la Fougere, Christian
utue.personen.roh	Reimold, Matthias
dcterms.isPartOf.ZSTitelID	European Journal of Nuclear Medicine and Molecular Imaging	de_DE
dcterms.isPartOf.ZS-Issue	11	de_DE
dcterms.isPartOf.ZS-Volume	46	de_DE
utue.fakultaet	04 Medizinische Fakultät	de_DE
utue.fakultaet	08 Zentrale, interfakultäre und fakultätsübergreifende Einrichtungen	de_DE