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dc.contributor.authorSabidussi, E.
dc.contributor.authorNicastro, Michele
dc.contributor.authorBazrafkan, Shabab
dc.contributor.authorBeirinckx, Quinten
dc.contributor.authorJeurissen, Ben
dc.contributor.authorden dekker, Arnold Jan
dc.contributor.authorPoot, D.H.J.
dc.date.accessioned2021-10-27T17:22:55Z
dc.date.available2021-10-27T17:22:55Z
dc.date.issued2019
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/33919
dc.sourceIIOimport
dc.titleA deep learning approach to T1 mapping in quantitative MRI
dc.typeMeeting abstract
dc.contributor.imecauthorNicastro, Michele
dc.contributor.imecauthorBazrafkan, Shabab
dc.contributor.imecauthorBeirinckx, Quinten
dc.contributor.imecauthorJeurissen, Ben
dc.source.peerreviewyes
dc.source.conference36th Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine & Biology, Rotterdam, The Netherlands
dc.source.conferencedate3/10/2019
dc.source.conferencelocationRotterdam The Netherlands
dc.identifier.urlhttps://doi.org/10.1007/s10334-019-00754-2
imec.availabilityPublished - imec
imec.internalnotesMagnetic Resonance Materials in Physics, Biology and Medicine. Vol. 32 (Suppl. 1) Issue S09.05


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