Sensitivity analysis for electrical detection of aortic dissection

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

In medical and patient-specific applications, uncertainty quantification and sensitivity analysis are indispensable in the process of diagnosis and decision-making. For the identification of an aortic dissection, a 3D FEM model is used to simulate an appropriate measurement setup. Based on this model, a method to evaluate the uncertainty distribution of a pre-defined parameter set is proposed. In particular, sensitivity analysis is divided into two steps. The first step involves an initial screening using the Morris method. In the second step, a sensitivity analysis is performed through a variance-based setting. Here, Polynomial Chaos Expansion (PCE) surrogate model is used. Subsequent post-processing on the study allows the computation of the representative sensitivity indices.
Original languageEnglish
Title of host publicationProceedings in Applied Mathematics and Mechanics
PublisherWiley-VCH
Number of pages2
Publication statusAccepted/In press - 2019
EventGAMM 2019: 90th Annual Meeting of the International Association of Applied Mathematics and Mechanics - Vienna, Austria
Duration: 18 Feb 201922 Feb 2019

Conference

ConferenceGAMM 2019
CountryAustria
CityVienna
Period18/02/1922/02/19

Fingerprint

Dissection
Sensitivity analysis
Uncertainty analysis
Chaos theory
Identification (control systems)
Screening
Decision making
Polynomials
Finite element method
Processing

Cite this

Sensitivity analysis for electrical detection of aortic dissection. / Melito, Gian Marco; Badeli, Vahid; Reinbacher-Köstinger, Alice; Ellermann, Katrin.

Proceedings in Applied Mathematics and Mechanics. Wiley-VCH , 2019.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Melito, GM, Badeli, V, Reinbacher-Köstinger, A & Ellermann, K 2019, Sensitivity analysis for electrical detection of aortic dissection. in Proceedings in Applied Mathematics and Mechanics. Wiley-VCH , GAMM 2019, Vienna, Austria, 18/02/19.
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AB - In medical and patient-specific applications, uncertainty quantification and sensitivity analysis are indispensable in the process of diagnosis and decision-making. For the identification of an aortic dissection, a 3D FEM model is used to simulate an appropriate measurement setup. Based on this model, a method to evaluate the uncertainty distribution of a pre-defined parameter set is proposed. In particular, sensitivity analysis is divided into two steps. The first step involves an initial screening using the Morris method. In the second step, a sensitivity analysis is performed through a variance-based setting. Here, Polynomial Chaos Expansion (PCE) surrogate model is used. Subsequent post-processing on the study allows the computation of the representative sensitivity indices.

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