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Status: Bibliographieeintrag

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Verfasst von:Salehi Ravesh, Mona [VerfasserIn]   i
 Brix, G. [VerfasserIn]   i
 Laun, Frederik B. [VerfasserIn]   i
 Kuder, Tristan Anselm [VerfasserIn]   i
 Puderbach, Michael [VerfasserIn]   i
 Ley-Zaporozhan, Julia [VerfasserIn]   i
 Ley, S. [VerfasserIn]   i
 Fieselmann, A. [VerfasserIn]   i
 Herrmann, M. F. [VerfasserIn]   i
 Schranz, W. [VerfasserIn]   i
 Semmler, W. [VerfasserIn]   i
 Risse, Frank [VerfasserIn]   i
Titel:Quantification of pulmonary microcirculation by dynamic contrast-enhanced magnetic resonance imaging
Titelzusatz:comparison of four regularization methods
Verf.angabe:M. Salehi Ravesh, G. Brix, F.B. Laun, T.A. Kuder, M. Puderbach, J. Ley-Zaporozhan, S. Ley, A. Fieselmann, M.F. Herrmann, W. Schranz, W. Semmler, and F. Risse
Jahr:2013
Umfang:12 S.
Fussnoten:Published online 1 March 2012 ; Gesehen am 16.12.2021
Titel Quelle:Enthalten in: Magnetic resonance in medicine
Ort Quelle:New York, NY [u.a.] : Wiley-Liss, 1984
Jahr Quelle:2013
Band/Heft Quelle:69(2013), 1 vom: Jan., Seite 188-199
ISSN Quelle:1522-2594
Abstract:Tissue microcirculation can be quantified by a deconvolution analysis of concentration-time curves measured by dynamic contrast-enhanced magnetic resonance imaging. However, deconvolution is an ill-posed problem, which requires regularization of the solutions. In this work, four algebraic deconvolution/regularization methods were evaluated: truncated singular value decomposition and generalized Tikhonov regularization (GTR) in combination with the L-curve criterion, a modified LCC (GTR-MLCC), and a response function model that takes a-priori knowledge into account. To this end, dynamic contrast-enhanced magnetic resonance imaging data sets were simulated by an established physiologically reference model for different signal-to-noise ratios and measured on a 1.5-T system in the lung of 10 healthy volunteers and 20 patients. Analysis of both the simulated and measured dynamic contrast-enhanced magnetic resonance imaging datasets revealed that GTR in combination with the L-curve criterion does not yield reliable and clinically useful results. The three other deconvolution/regularization algorithms resulted in almost identical microcirculatory parameter estimates for signal-to-noise ratios > 10. At low signal-to-noise ratios levels (<10) typically occurring in pathological lung regions, GTR in combination with a modified L-curve criterion approximates the true response function much more accurately than truncated singular value decomposition and GTR in combination with response function model with a difference in accuracy of up to 76%. In conclusion, GTR in combination with a modified L-curve criterion is recommended for the deconvolution of dynamic contrast-enhanced magnetic resonance imaging curves measured in the lung parenchyma of patients with highly heterogeneous signal-to-noise ratios. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc.
DOI:doi:10.1002/mrm.24220
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext ; Verlag: https://doi.org/10.1002/mrm.24220
 Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/mrm.24220
 DOI: https://doi.org/10.1002/mrm.24220
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:lung perfusion
 model-free algebraic deconvolution
 quantitative analysis
 Tikhonov regularization
K10plus-PPN:178235929X
Verknüpfungen:→ Zeitschrift

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