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On the stable estimation of flow geometry and wall shear stress from magnetic resonance images

Egger, Herbert ; Teschner, Gabriel (2021)
On the stable estimation of flow geometry and wall shear stress from magnetic resonance images.
In: Inverse Problems, 35 (9)
doi: 10.1088/1361-6420/ab23d5
Artikel, Bibliographie

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Kurzbeschreibung (Abstract)

We consider the stable reconstruction of flow geometry and wall shear stress from measurements obtained by magnetic resonance imaging (MRI). As noted in a review article by Petersson, most approaches considered so far in the literature seem to not be satisfactory. We therefore propose a systematic reconstruction procedure that allows us to obtain stable estimates of flow geometry and wall shear stress and we are able to quantify the reconstruction errors in terms of bounds for the measurement errors under reasonable smoothness assumptions. A complete analysis of our approach is given in the framework of regularization methods. In addition, we briefly discuss the implementation of our method and we demonstrate its viability, accuracy, and regularizing properties for experimental data.

Typ des Eintrags: Artikel
Erschienen: 2021
Autor(en): Egger, Herbert ; Teschner, Gabriel
Art des Eintrags: Bibliographie
Titel: On the stable estimation of flow geometry and wall shear stress from magnetic resonance images
Sprache: Englisch
Publikationsjahr: 2021
Verlag: IOP Publishing
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Inverse Problems
Jahrgang/Volume einer Zeitschrift: 35
(Heft-)Nummer: 9
Kollation: 23 Seiten
DOI: 10.1088/1361-6420/ab23d5
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Kurzbeschreibung (Abstract):

We consider the stable reconstruction of flow geometry and wall shear stress from measurements obtained by magnetic resonance imaging (MRI). As noted in a review article by Petersson, most approaches considered so far in the literature seem to not be satisfactory. We therefore propose a systematic reconstruction procedure that allows us to obtain stable estimates of flow geometry and wall shear stress and we are able to quantify the reconstruction errors in terms of bounds for the measurement errors under reasonable smoothness assumptions. A complete analysis of our approach is given in the framework of regularization methods. In addition, we briefly discuss the implementation of our method and we demonstrate its viability, accuracy, and regularizing properties for experimental data.

Sachgruppe der Dewey Dezimalklassifikatin (DDC): 500 Naturwissenschaften und Mathematik > 510 Mathematik
Fachbereich(e)/-gebiet(e): 04 Fachbereich Mathematik
04 Fachbereich Mathematik > Numerik und wissenschaftliches Rechnen
Hinterlegungsdatum: 02 Aug 2024 12:36
Letzte Änderung: 02 Aug 2024 12:36
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