A flexible framework for sequential estimation of model parameters in computational hemodynamics - Inria - Institut national de recherche en sciences et technologies du numérique
Article Dans Une Revue Advanced Modeling and Simulation in Engineering Sciences Année : 2020

A flexible framework for sequential estimation of model parameters in computational hemodynamics

Résumé

A major challenge in constructing three dimensional patient specific hemodynamic models is the calibration of model parameters to match patient data on flow, pressure, wall motion, etc. acquired in the clinic. Current workflows are manual and time-consuming. This work presents a flexible computational framework for model parameter estimation in cardiovascular flows that relies on the following fundamental contributions. (i) A Reduced-Order Unscented Kalman Filter (ROUKF) model for data assimilation for wall material and simple lumped parameter network (LPN) boundary condition model parameters. (ii) A constrained least squares augmentation (ROUKF-CLS) for more complex LPNs. (iii) A "Netlist" implementation, supporting easy filtering of parameters in such complex LPNs. The ROUKF algorithm is demonstrated using non-invasive patient-specific data on anatomy, flow and pressure from a healthy volunteer. The ROUKF-CLS algorithm is demonstrated using synthetic data on a coronary LPN. The methods described in this paper have been implemented as part of the CRIMSON hemodynamics software package.
Fichier principal
Vignette du fichier
s40323-020-00186-x.pdf (5.86 Mo) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-03113107 , version 1 (18-01-2021)

Identifiants

Citer

Christopher J Arthurs, Nan Xiao, Philippe Moireau, Tobias Schaeffter, Alberto Alberto Figueroa. A flexible framework for sequential estimation of model parameters in computational hemodynamics. Advanced Modeling and Simulation in Engineering Sciences, 2020, 7, ⟨10.1186/s40323-020-00186-x⟩. ⟨hal-03113107⟩
129 Consultations
128 Téléchargements

Altmetric

Partager

More