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Detail publikace
DAŇKOVÁ, M. RAJMIC, P.
Originální název
Debiasing incorporated into reconstruction of low-rank modelled dynamic MRI data
Typ
abstrakt
Jazyk
angličtina
Originální abstrakt
Reconstruction of undersampled dynamic magnetic resonance imaging (MRI) data can be treated as a compressed sensing (CS) problem. Reconstruction using CS proved to be very useful in the area of MRI, but the estimates are biased due to convex relaxation of sparsity measures. Debiasing is a procedure usually carried out by the least squares method after the CS solution has been found. We show a method which debiases the estimates within a single procedure, when the CS problem, arising from the perfusion MRI analysis (DCE-MRI), involves a low-rank prior.
Klíčová slova
MRI, compressed sensing, perfusion, L+S model
Autoři
DAŇKOVÁ, M.; RAJMIC, P.
Vydáno
24. 8. 2016
Místo
Aalborg, Dánsko
Strany od
53
Strany do
55
Strany počet
3
URL
https://www.itwist16.es.aau.dk/digitalAssets/223/223252_dankovamarie-poster.pdf
BibTex
@misc{BUT128073, author="Marie {Mangová} and Pavel {Rajmic}", title="Debiasing incorporated into reconstruction of low-rank modelled dynamic MRI data", year="2016", pages="53--55", address="Aalborg, Dánsko", url="https://www.itwist16.es.aau.dk/digitalAssets/223/223252_dankovamarie-poster.pdf", note="abstract" }