Detail publikace

MODELLING IN PERFUSION MR IMAGING

VÁLKOVÁ, H. KRATOCHVÍLA, J.

Originální název

MODELLING IN PERFUSION MR IMAGING

Český název

MODELLING IN PERFUSION MR IMAGING

Typ

článek ve sborníku

Jazyk

cs

Originální abstrakt

This paper deals with quantitative perfusion analysis of dynamic contrast enhanced magnetic resonance data. The perfusion parameter estimation method is based on approximation of tissue concentration time sequences with convolution models. The method is evaluated on synthetic data and illustrated on clinical data of the renal cell carcinoma patient. The main contribution of the article is the inclusion of dispersion model to capture the signal changes on the way from artery to remote tissues.

Český abstrakt

This paper deals with quantitative perfusion analysis of dynamic contrast enhanced magnetic resonance data. The perfusion parameter estimation method is based on approximation of tissue concentration time sequences with convolution models. The method is evaluated on synthetic data and illustrated on clinical data of the renal cell carcinoma patient. The main contribution of the article is the inclusion of dispersion model to capture the signal changes on the way from artery to remote tissues.

Klíčová slova

Perfusion imaging, DCE-MRI, arterial input function, tissue residual function, dispersion of arterial input function, curve modelling

Rok RIV

2014

Vydáno

24.04.2014

ISBN

978-80-214-4923-7

Kniha

Proceedings of the 20th Conference Student EEICT 2014

Strany od

57

Strany do

59

Strany počet

3

BibTex


@inproceedings{BUT108486,
  author="Hana {Válková} and Jiří {Kratochvíla}",
  title="MODELLING IN PERFUSION MR IMAGING",
  annote="This paper deals with quantitative perfusion analysis of dynamic contrast enhanced magnetic resonance data. The perfusion parameter estimation method is based on approximation of tissue concentration time sequences with convolution models. The method is evaluated on synthetic data and illustrated on clinical data of the renal cell carcinoma patient. The main contribution of the article is the inclusion of dispersion model to capture the signal changes on the way from artery to remote tissues.",
  booktitle="Proceedings of the 20th Conference Student EEICT 2014",
  chapter="108486",
  howpublished="print",
  year="2014",
  month="april",
  pages="57--59",
  type="conference paper"
}