Publication detail

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

DAŇKOVÁ, M. RAJMIC, P.

Original Title

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

Type

abstract

Language

English

Original Abstract

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.

Keywords

MRI, compressed sensing, perfusion, L+S model

Authors

DAŇKOVÁ, M.; RAJMIC, P.

Released

24. 8. 2016

Location

Aalborg, Dánsko

Pages from

53

Pages to

55

Pages count

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"
}