91 citations · 351 across the 10 of their papers we have counts for
11 papers
Non-Intrusive Parametrized-Background Data-Weak Reconstruction of Cardiac Displacement Fields from Sparse MRI-like Observations
Francesco C. Mantegazza, Federica Caforio, Christoph Augustin +3
Personalized cardiac diagnostics require accurate reconstruction of myocardial displacement fields from sparse clinical imaging data, yet current methods often demand intrusive acc…
Physics-informed neural network estimation of active material properties in time-dependent cardiac biomechanical models
Matthias Höfler, Francesco Regazzoni, Stefano Pagani +5
Active stress models in cardiac biomechanics account for the mechanical deformation caused by muscle activity, thus providing a link between the electrophysiological and mechanical…
Physics-informed Neural Network Estimation of Material Properties in Soft Tissue Nonlinear Biomechanical Models
Federica Caforio, Francesco Regazzoni, Stefano Pagani +5
The development of biophysical models for clinical applications is rapidly advancing in the research community, thanks to their predictive nature and their ability to assist the in…
Global Sensitivity Analysis of Four Chamber Heart Hemodynamics Using Surrogate Models
Elias Karabelas, Stefano Longobardi, Jana Fuchsberger +7
Computational Fluid Dynamics (CFD) is used to assist in designing artificial valves and planning procedures, focusing on local flow features. However, assessing the impact on overa…
An accurate, robust, and efficient finite element framework for anisotropic, nearly and fully incompressible elasticity
Elias Karabelas, Matthias A. F. Gsell, Gundolf Haase +2
Fiber-reinforced soft biological tissues are typically modeled as hyperelastic, anisotropic, and nearly incompressible materials. To enforce incompressibility a multiplicative spli…
A computationally efficient physiologically comprehensive 3D-0D closed-loop model of the heart and circulation
Christoph M. Augustin, Matthias A. F. Gsell, Elias Karabelas +5
Computer models of cardiac electro-mechanics (EM) show promise as an effective means for quantitative analysis of clinical data and, potentially, for predicting therapeutic respons…