Introducing a Linear Gamma Variate Fit to Measure Pulmonary Perfusion with Electrical Impedance Tomography
The indicator dilution method (IDM) is one approach to measure pulmonary perfusion using Electrical Impedance Tomography (EIT). To be able to calculate perfusion parameters and to increase robustnes, it is necessary to approximate and then to separate the components of the measured signals. The comp...
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De Gruyter
2020
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oai:doaj.org-article:34723b5776e141cb94572ee6ddcce7f02021-12-05T14:10:42ZIntroducing a Linear Gamma Variate Fit to Measure Pulmonary Perfusion with Electrical Impedance Tomography2364-550410.1515/cdbme-2020-3089https://doaj.org/article/34723b5776e141cb94572ee6ddcce7f02020-09-01T00:00:00Zhttps://doi.org/10.1515/cdbme-2020-3089https://doaj.org/toc/2364-5504The indicator dilution method (IDM) is one approach to measure pulmonary perfusion using Electrical Impedance Tomography (EIT). To be able to calculate perfusion parameters and to increase robustnes, it is necessary to approximate and then to separate the components of the measured signals. The component referring to the passage of the injected bolus through the pixels can be modeled as a gamma variate function, its parameters are often determined using nonlinear optimization algorithms. In this paper, we introduce a linear approach that enables higher robustnes and faster computation, and compare the linear and nonlinear fitting approach on data of an animal study.Schuderer FelixKircher MichaelDössel OlafStender BirgitBluth ThomasGama de Abreu MarceloDe Gruyterarticleelectrical impedance tomographyindicator dilutiongamma variateleast squaresparameter optimizationpulmonary perfusionMedicineRENCurrent Directions in Biomedical Engineering, Vol 6, Iss 3, Pp 345-348 (2020) |
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electrical impedance tomography indicator dilution gamma variate least squares parameter optimization pulmonary perfusion Medicine R |
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electrical impedance tomography indicator dilution gamma variate least squares parameter optimization pulmonary perfusion Medicine R Schuderer Felix Kircher Michael Dössel Olaf Stender Birgit Bluth Thomas Gama de Abreu Marcelo Introducing a Linear Gamma Variate Fit to Measure Pulmonary Perfusion with Electrical Impedance Tomography |
description |
The indicator dilution method (IDM) is one approach to measure pulmonary perfusion using Electrical Impedance Tomography (EIT). To be able to calculate perfusion parameters and to increase robustnes, it is necessary to approximate and then to separate the components of the measured signals. The component referring to the passage of the injected bolus through the pixels can be modeled as a gamma variate function, its parameters are often determined using nonlinear optimization algorithms. In this paper, we introduce a linear approach that enables higher robustnes and faster computation, and compare the linear and nonlinear fitting approach on data of an animal study. |
format |
article |
author |
Schuderer Felix Kircher Michael Dössel Olaf Stender Birgit Bluth Thomas Gama de Abreu Marcelo |
author_facet |
Schuderer Felix Kircher Michael Dössel Olaf Stender Birgit Bluth Thomas Gama de Abreu Marcelo |
author_sort |
Schuderer Felix |
title |
Introducing a Linear Gamma Variate Fit to Measure Pulmonary Perfusion with Electrical Impedance Tomography |
title_short |
Introducing a Linear Gamma Variate Fit to Measure Pulmonary Perfusion with Electrical Impedance Tomography |
title_full |
Introducing a Linear Gamma Variate Fit to Measure Pulmonary Perfusion with Electrical Impedance Tomography |
title_fullStr |
Introducing a Linear Gamma Variate Fit to Measure Pulmonary Perfusion with Electrical Impedance Tomography |
title_full_unstemmed |
Introducing a Linear Gamma Variate Fit to Measure Pulmonary Perfusion with Electrical Impedance Tomography |
title_sort |
introducing a linear gamma variate fit to measure pulmonary perfusion with electrical impedance tomography |
publisher |
De Gruyter |
publishDate |
2020 |
url |
https://doaj.org/article/34723b5776e141cb94572ee6ddcce7f0 |
work_keys_str_mv |
AT schudererfelix introducingalineargammavariatefittomeasurepulmonaryperfusionwithelectricalimpedancetomography AT kirchermichael introducingalineargammavariatefittomeasurepulmonaryperfusionwithelectricalimpedancetomography AT dosselolaf introducingalineargammavariatefittomeasurepulmonaryperfusionwithelectricalimpedancetomography AT stenderbirgit introducingalineargammavariatefittomeasurepulmonaryperfusionwithelectricalimpedancetomography AT bluththomas introducingalineargammavariatefittomeasurepulmonaryperfusionwithelectricalimpedancetomography AT gamadeabreumarcelo introducingalineargammavariatefittomeasurepulmonaryperfusionwithelectricalimpedancetomography |
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