Multiparametric Oncologic Hybrid Imaging: Machine Learning Challenges and Opportunities

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dc.contributor.author Hepp, Tobias
dc.contributor.author Küstner, Thomas
dc.contributor.author Seith, Ferdinand Frederic
dc.date.accessioned 2023-01-24T10:46:54Z
dc.date.available 2023-01-24T10:46:54Z
dc.date.issued 2022
dc.identifier.issn 1438-9029
dc.identifier.uri http://hdl.handle.net/10900/135594
dc.language.iso en de_DE
dc.publisher Georg Thieme Verlag KG de_DE
dc.relation.uri http://dx.doi.org/10.1055/a-1718-4128 de_DE
dc.subject.ddc 610 de_DE
dc.title Multiparametric Oncologic Hybrid Imaging: Machine Learning Challenges and Opportunities de_DE
dc.type Article de_DE
utue.quellen.id 20220728000000_01885
utue.publikation.seiten 605-612 de_DE
utue.personen.roh Kuestner, Thomas
utue.personen.roh Hepp, Tobias
utue.personen.roh Seith, Ferdinand
dcterms.isPartOf.ZSTitelID Rofo - Fortschritte auf dem Gebiet der Rontgenstrahlen und der Bildgebenden Verfahren de_DE
dcterms.isPartOf.ZS-Issue 6 de_DE
dcterms.isPartOf.ZS-Volume 194 de_DE
utue.fakultaet 04 Medizinische Fakultät de_DE


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