Detail publikace

Absolute ultrasound perfusion parameter quantification of a tissue-mimicking phantom using bolus tracking

Originální název

Absolute ultrasound perfusion parameter quantification of a tissue-mimicking phantom using bolus tracking

Anglický název

Absolute ultrasound perfusion parameter quantification of a tissue-mimicking phantom using bolus tracking

Jazyk

en

Originální abstrakt

This study presents three methods for absolute quantification in ultrasound perfusion analysis based on bolus tracking. The first two methods deconvolve the perfusion time sequence with a measured AIF, using a nonparametric or a parametric model of the tissue residue function, respectively. The third method is a simplified approach avoiding deconvolution by assuming a narrow AIF. A phantom with a dialyzer filter as a tissue-mimicking model was used for evaluation. Estimated mean transit times and blood volumes were compared with the theoretical values. A match with a maximum error of 12% was achieved.

Anglický abstrakt

This study presents three methods for absolute quantification in ultrasound perfusion analysis based on bolus tracking. The first two methods deconvolve the perfusion time sequence with a measured AIF, using a nonparametric or a parametric model of the tissue residue function, respectively. The third method is a simplified approach avoiding deconvolution by assuming a narrow AIF. A phantom with a dialyzer filter as a tissue-mimicking model was used for evaluation. Estimated mean transit times and blood volumes were compared with the theoretical values. A match with a maximum error of 12% was achieved.

BibTex


@article{BUT114552,
  author="Martin {Mézl} and Radovan {Jiřík} and Vratislav {Harabiš} and Radim {Kolář} and Michal {Standara} and Kim {Nylund} and Odd Helge {Gilja} and Torfinn {Taxt}",
  title="Absolute ultrasound perfusion parameter quantification of a tissue-mimicking phantom using bolus tracking",
  annote="This study presents three methods for absolute quantification in ultrasound perfusion analysis based on bolus tracking. The first two methods deconvolve the perfusion time sequence with a measured AIF, using a nonparametric or a parametric model of the tissue residue function, respectively. The third method is a simplified approach avoiding deconvolution by assuming a narrow AIF. A phantom with a dialyzer filter as a tissue-mimicking model was used for evaluation. Estimated mean transit times and blood volumes were compared with the theoretical values. A match with a maximum error of 12% was achieved.",
  address="IEEE",
  chapter="114552",
  doi="10.1109/TUFFC.2014.006896",
  institution="IEEE",
  number="5",
  volume="62",
  year="2015",
  month="may",
  pages="983--987",
  publisher="IEEE",
  type="journal article in Web of Science"
}