Detail publikace

Debiasing incorporated into reconstruction of low-rank modelled dynamic MRI data

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"
}