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- Q91801625 description "article scientifique (publié 2020)" @default.
- Q91801625 description "articolo scientifico (pubblicato il 2020)" @default.
- Q91801625 description "artigo científico (publicado na 2020)" @default.
- Q91801625 description "artikull shkencor i botuar më 01 janar 2020" @default.
- Q91801625 description "artículo científico publicado en 2020" @default.
- Q91801625 description "artículu científicu espublizáu en xineru de 2020" @default.
- Q91801625 description "im Jahr 2020 veröffentlichter wissenschaftlicher Artikel" @default.
- Q91801625 description "scientific article published on 01 January 2020" @default.
- Q91801625 description "wetenschappelijk artikel" @default.
- Q91801625 description "наукова стаття, опублікована 1 січня 2020" @default.
- Q91801625 description "научна статия" @default.
- Q91801625 name "Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks" @default.
- Q91801625 name "Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks" @default.
- Q91801625 name "Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks" @default.
- Q91801625 type Item @default.
- Q91801625 label "Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks" @default.
- Q91801625 label "Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks" @default.
- Q91801625 label "Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks" @default.
- Q91801625 prefLabel "Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks" @default.
- Q91801625 prefLabel "Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks" @default.
- Q91801625 prefLabel "Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks" @default.
- Q91801625 P1433 Q91801625-EF56F841-247D-40FA-A756-87D34A22587E @default.
- Q91801625 P1476 Q91801625-0A951CE6-D6A3-440E-A1C3-946EB6C8459D @default.
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- Q91801625 P356 Q91801625-C25797AC-AD88-484E-860E-4FA043127F48 @default.
- Q91801625 P433 Q91801625-8D6905C1-3E79-46D5-AE46-C3D3CAC62CF0 @default.
- Q91801625 P478 Q91801625-5D77542F-DC03-4F7E-B693-8F19E9C09711 @default.
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- Q91801625 P921 Q91801625-6F18E1C3-133F-40B3-825C-F16DCCC216AF @default.
- Q91801625 P356 MP.13950 @default.
- Q91801625 P698 31816095 @default.
- Q91801625 P1433 Q15764251 @default.
- Q91801625 P1476 "Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks" @default.
- Q91801625 P2093 "Andreas Maier" @default.
- Q91801625 P2093 "Marc Kachelrieß" @default.
- Q91801625 P2093 "Michael Lell" @default.
- Q91801625 P2093 "Sabrina Dorn" @default.
- Q91801625 P2093 "Shiyang Hu" @default.
- Q91801625 P2093 "Shuqing Chen" @default.
- Q91801625 P2093 "Xia Zhong" @default.
- Q91801625 P304 "552-562" @default.
- Q91801625 P31 Q13442814 @default.
- Q91801625 P356 "10.1002/MP.13950" @default.
- Q91801625 P433 "2" @default.
- Q91801625 P478 "47" @default.
- Q91801625 P577 "2020-01-01T00:00:00Z" @default.
- Q91801625 P698 "31816095" @default.
- Q91801625 P921 Q17084460 @default.