4 papers
Physics-constrained identification of graph-based thermal networks for spacecraft digital twins
Luca Sosta, Carlo Ciancarelli, Leonardo Marini +3
Reconstructing a thermal model capable of efficiently simulating the behavior of a spacecraft from sparse and localized temperature measurements remains a challenging task. To addr…
Learning geometry-dependent lead-field operators for forward ECG modeling
Arsenii Dokuchaev, Francesca Bonizzoni, Stefano Pagani +2
Modern forward electrocardiogram (ECG) computational models rely on an accurate representation of the torso domain. The lead-field method enables fast ECG simulations while preserv…
Deformable registration and generative modelling of aortic anatomies by auto-decoders and neural ODEs
Riccardo Tenderini, Luca Pegolotti, Fanwei Kong +4
This work introduces AD-SVFD, a deep learning model for the deformable registration of vascular shapes to a pre-defined reference and for the generation of synthetic anatomies. AD-…
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…