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Communication Dans Un Congrès Année : 2023

Fluid-structure interaction calibration from 4D-flow MRI data

Résumé

Patient-specific blood flow simulations are intensively fostered as a way of providing predictive mech- anistic biomarkers for thoracic aneurysms treatment from medical imaging data. Such biomarkers are generally sensitive to the underlying flow model (pure fluid model, fluid-structure interaction, bound- ary conditions, etc.). In the past 20 years, 4D-flow MRI has become a promising image data modality for blood flow model personalization, since it is non-invasive and provides a time-resolved three-dimensional encoding of the blood velocity field. This work is devoted to the state estimation of a fluid-structure interaction (FSI) model of aortic blood flow using 4D-flow MRI data. We propose a state estimation approach which avoids lumped pa- rameter models of boundary conditions through a unique continuation approach coupled to a Luenberger observer. The capabilities of the proposed approach will be assessed in a numerical study involving synthetic and clinical data.
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Dates et versions

hal-04397115 , version 1 (16-01-2024)

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  • HAL Id : hal-04397115 , version 1

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Muriel Boulakia, Miguel Angel Fernández, Damiano Lombardi, Mihai Nechita, Mocia Agbalessi. Fluid-structure interaction calibration from 4D-flow MRI data. CFC 2023 - IACM Computational Fluids Conference, Apr 2023, Cannes, France. ⟨hal-04397115⟩
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