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

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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


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