Konstantinos Mountris
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Multiphysics modelling and neural networks synergy to enhance the outcome of robotic catheter ablation for the treatment of atrial fibrillation
Open Date: 2022-01-01
Close Date: 2023-12-31
Articles (5)
We present the meshfree mixed collocation method (MCM) for cardiac electrophysiology simulation. Capitalizing on the meshfree property of MCM, we introduce an immersed grid approach for automated generation of meshfree node grids from medical image data. This approach allows us to avoid the time-consuming mesh generation and processing that mesh-based methods like the finite element method (FEM) require. We employ the MCM to solve the cardiac monodomain model considering electrical propagation in 2D tissue sheets, 3D tissue slabs, and a realistic biventricular anatomy. We demonstrate that the solutions obtained by the MCM are in good agreement with the FEM, particularly when immersed grid is used. These findings confirm the suitability of the MCM for cardiac electrophysiology simulation and make the MCM a promising alternative to the FEM for cardiac electrical investigations.
Year:
2023
Year:
2022
Year:
2021
Year:
2020
Year:
2020
Collaborators (7)
Panagiotis Papadimitroulas
University of Patras
Rafael Sebastian
Full Professor
University of Valencia
Maxime Sermesant
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Esther Pueyo
Universidad de Zaragoza
Oscar Camara
Full Professor
Universitat Pompeu Fabra
George Kagadis
Professor of Medical Physics - Medical Informatics
University of Patras
Julien Bert
Research Scientist, head of the research group: Dose optimisation for image guided therapy
University of Brest
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