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Fast many-core solvers for the Eikonal equations in cardiovascular simulations

Daniel Ganellari, Gundolf Haase
2016 2016 International Conference on High Performance Computing & Simulation (HPCS)  
Due to the splitting of the wave front (described by the Eikonal equations), the parallel version results in a slightly different convergence history and in minor differences in the solution.  ...  We will address the implementation of an Eikonal solver for Shared Memory (OpenMP) with a low memory footprint.  ...  ACKNOWLEDGEMENT The authors gratefully acknowledge support from Erasmus Mundus JoinEUsee PENTA scholarship and from NAWI Graz.  ... 
doi:10.1109/hpcsim.2016.7568347 dblp:conf/ieeehpcs/GanellariH16 fatcat:6ac2s72yazbpddzaptlggtl33q

A massively parallel Eikonal solver on unstructured meshes

Daniel Ganellari, Gundolf Haase, Gerhard Zumbusch
2018 Computing and Visualization in Science  
Keywords Eikonal equation · GPU · domain decomposition · tetrahedral mesh · parallel algorithm Introduction Recent work in [1-3] has shown that building an efficient 3D tetrahedral Eikonal solver for multi-core  ...  We use the fast iterative method (FIM) [1, 4, 5] for solving the Eikonal equation, especially the version by Fu, Kirby and Whitaker [1] wherein the memory footprint has been reduced by storing temporarily  ...  The application background for our paper are cardiovascular simulations that use Eikonal solvers for determining the initial excitation pattern in a human heart [6] .  ... 
doi:10.1007/s00791-018-0288-z fatcat:ao6oix4ojffobfyyea2ty44bda

A Re-Engineered Software Interface and Workflow for the Open-Source SimVascular Cardiovascular Modeling Package

Hongzhi Lan, Adam Updegrove, Nathan M. Wilson, Gabriel D. Maher, Shawn C. Shadden, Alison L. Marsden
2018 Journal of Biomechanical Engineering  
Patient-specific simulation plays an important role in cardiovascular disease research, diagnosis, surgical planning and medical device design, as well as education in cardiovascular biomechanics.  ...  We also briefly describe our recent experiences using SimVascular in the classroom for bioengineering education.  ...  Funding Data Directorate for Computer and Information Science and Engineering (Grant Nos. 1339824 and 1663671).  ... 
doi:10.1115/1.4038751 pmid:29238826 pmcid:PMC5816252 fatcat:t4issy2ofrdfdgjwvon5uoj654

Towards an interactive electromechanical model of the heart

H. Talbot, S. Marchesseau, C. Duriez, M. Sermesant, S. Cotin, H. Delingette
2013 Interface Focus  
In this work, we develop an interactive framework for rehearsal of and training in cardiac catheter ablation, and for planning cardiac resynchronization therapy.  ...  Second, a mechanical simulation is then coupled to the electrophysiological signals to produce realistic motion of the heart.  ...  In this work, the authors explained that traditional FEMs could not offer fast electrophysiology simulations.  ... 
doi:10.1098/rsfs.2012.0091 pmid:24427533 pmcid:PMC3638488 fatcat:tn54w3o3qvfjfpgtmcfg6zsf2u

3D Fluid-Structure Interaction Simulation of Aortic Valves Using a Unified Continuum ALE FEM Model

Jeannette H. Spühler, Johan Jansson, Niclas Jansson, Johan Hoffman
2018 Frontiers in Physiology  
In previous work, we simulated the blood flow in the left ventricle of the heart.  ...  Due to advances in medical imaging, computational fluid dynamics algorithms and high performance computing, computer simulation is developing into an important tool for understanding the relationship between  ...  FUNDING The authors would like to acknowledge the financial support from the Swedish Foundation for Strategic Research, the Swedish Research Council and the European Research Council -ERC Starting Grant  ... 
doi:10.3389/fphys.2018.00363 pmid:29713288 pmcid:PMC5911501 fatcat:uwb4mxz7onfzdpq43jczv3t5ze

An accurate, robust, and efficient finite element framework for anisotropic, nearly and fully incompressible elasticity [article]

Elias Karabelas, Matthias A. F. Gsell, Gundolf Haase, Gernot Plank, Christoph M. Augustin
2021 arXiv   pre-print
In this paper, we present novel methods to overcome locking phenomena for anisotropic materials using stabilized P1-P1 elements.  ...  In several benchmark problems we compare the approach to standard linear elements and show the accuracy and versatility of the methods to simulate anisotropic, nearly and fully incompressible materials  ...  Additionally, the research was supported by the Grants F3210-N18 and I2760-B30 from the Austrian Science Fund (FWF) and a BioTechMed Graz flagship award "ILearnHeart" to GP.  ... 
arXiv:2111.00612v1 fatcat:xez7danwlbbt5imaoeah7m423u

Image-Based Personalization of Cardiac Anatomy for Coupled Electromechanical Modeling

A. Crozier, C. M. Augustin, A. Neic, A. J. Prassl, M. Holler, T. E. Fastl, A. Hennemuth, K. Bredies, T. Kuehne, M. J. Bishop, S. A. Niederer, G. Plank
2015 Annals of Biomedical Engineering  
In this paper, we review the state of the art in image-based personalization of cardiac anatomy for biophysically detailed, strongly coupled EM modeling, and present our own tools for the automatic building  ...  Our method relies on using high resolution unstructured meshes for discretizing both physics, electrophysiology and mechanics, in combination with efficient, strongly scalable solvers necessary to deal  ...  The simulation of a single heartbeat took 235.3 minutes using 8 192 compute cores on the SuperMUC high performance computing (HPC) resource.  ... 
doi:10.1007/s10439-015-1474-5 pmid:26424476 pmcid:PMC4690840 fatcat:5q7gu6fgqbbmrcal6fmquygnn4

A fast computational model for the electrophysiology of the whole human heart [article]

Giulio Del Corso, Roberto Verzicco, Francesco Viola
2021 arXiv   pre-print
In this study we present a novel computational model for unprecedented simulations of the whole cardiac electrophysiology.  ...  The propagation of the action potential in these conductive media is governed by the bidomain/monodomain equations, which are discretized in space using an in-house finite volume method and coupled to  ...  Plank, Solvers for the cardiac bidomain equations, Progress in biophysics and molecular biology 96 (1-3) (2008) 3–18. [31] J. P. Wikswo Jr, S.-F. Lin, R. A.  ... 
arXiv:2112.12854v1 fatcat:k5qrbpcoojhbpdruad4ew3ppoe

The cardiovascular system: Mathematical modelling, numerical algorithms and clinical applications

A. Quarteroni, A. Manzoni, C. Vergara
2017 Acta Numerica  
In this review article we will address the two principal components of the cardiovascular system: arterial circulation and heart function.  ...  and ODE systems, proposing sound and efficient numerical methods for their approximation, and simulating both benchmark problems and clinically inspired problems.  ...  Acknowledgements The authors would like to thank P.  ... 
doi:10.1017/s0962492917000046 fatcat:loo2r2x3h5cgxdwhvd7r56kzu4

Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next [article]

Salvatore Cuomo, Vincenzo Schiano di Cola, Fabio Giampaolo, Gianluigi Rozza, Maziar Raissi, Francesco Piccialli
2022 arXiv   pre-print
Despite the wide range of applications for which PINNs have been used, by demonstrating their ability to be more feasible in some contexts than classical numerical techniques like Finite Element Method  ...  The review also attempts to incorporate publications on a broader range of collocation-based physics informed neural networks, which stars form the vanilla PINN, as well as many other variants, such as  ...  PPINN is composed of a fast coarse-grained (CG) solver and a finer solver given by PINN.  ... 
arXiv:2201.05624v4 fatcat:rezb3ctw3bamtfrswcwxlc2cvy

Proceedings of the FEniCS Conference 2017

Jack S. Hale
2017 Figshare  
Proceedings of the FEniCS Conference 2017 that took place 12-14 June 2017 at the University of Luxembourg, Luxembourg.You can cite individual articles in the proceedings using the following bibtex as a  ...  of the FEniCS Conference 2017  ...  Acknowledgements This work was supported in part by the Belgian Science Policy Office under grant IAP P7/02 and the Walloon Region under grant WIST3 DOMHEX. N.  ... 
doi:10.6084/m9.figshare.5086369.v1 fatcat:siyz4enqijbp5byzmdrvi75owm

Fast parameter calibration of a cardiac electromechanical model from medical images based on the unscented transform

Stéphanie Marchesseau, Hervé Delingette, Maxime Sermesant, Nicholas Ayache
2012 Biomechanics and Modeling in Mechanobiology  
We propose a fast automatic calibration method of the mechanical parameters of a complete electromechanical model of the heart based on a sensitivity analysis and the Unscented Transform algorithm.  ...  We show that the calibration method gives satisfying results by optimizing up to 5 parameters of the BCS model in only one iteration.  ...  Our implementation in SOFA first solves the coupled differential equations ( 2 ) with an Euler implicit solver, and then computes the required force fields and stiffness matrices for the global system  ... 
doi:10.1007/s10237-012-0446-z pmid:23064992 fatcat:oanxjwukpza2dms4hrq42e2uim

Nonlinear physics of electrical wave propagation in the heart: a review

Sergio Alonso, Markus Bär, Blas Echebarria
2016 Reports on progress in physics (Print)  
Numerous simulation and experimental studies during the last 20 years have addressed these topics.  ...  In this review we focus on the nonlinear dynamics of wave propagation in the heart with an emphasis on the theory of pulses, spirals and scroll waves and their instabilities in excitable media and their  ...  Acknowledgments We like to thank Thomas Niedermayer and two anonymous referee for a careful reading of the manuscript and making numerous suggestions, which helped to improve the manuscript.  ... 
doi:10.1088/0034-4885/79/9/096601 pmid:27517161 fatcat:rmqut4zmkzhfzdphvxnnbnypte

Personalising left-ventricular biophysical models of the heart using parametric physics-informed neural networks

Stefano Buoso, Thomas Joyce, Sebastian Kozerke
2021 Medical Image Analysis  
We present a parametric physics-informed neural network for the simulation of personalised left-ventricular biomechanics.  ...  ventricles and (ii) the cost function used for training is the energy potential functional specifically tailored for hyperelastic, anisotropic, nearly-incompressible active materials.  ...  Acknowledgements The authors acknowledge the financial support of the Swiss National Science Foundation (SNF ) [Grant CR23I3-166485], and of PHRT SWISSHEART Failure Network of the ETH Domain.  ... 
doi:10.1016/j.media.2021.102066 pmid:33951597 fatcat:a2x4srk6ubhqxihd2k3zgt6qa4

Software-based representation of selected benchmark hierarchies equipped with publically available data

Marcus Bannenberg, Patricia Barral, Jean-David Benamou, Federico Bianco, Andreas Binder, Sören Dittmer, Daniel Fernández Comesaña, Michele Girfoglio, Michael Günther, José Carlos Gutiérrez Pérez, Lena Hauberg-Lotte, Wilbert Ijzerman (+23 others)
2019 Zenodo  
Based on the multitude of industrial applications, benchmarks for model hierarchies will be created that will form a basis for the interdisciplinary research and for the training programme.  ...  These will be equipped with publically available data and will be used for training in modelling, model testing, reduced order modelling, error estimation, efficiency optimization in algorithmic approaches  ...  The simulation data from the solver is read into memory through many supported file formats.  ... 
doi:10.5281/zenodo.3474967 fatcat:by5nwr624jaqnbvc3iky6wzsua
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