Konstantinos Mountris

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University College London
Country flagUnited Kingdom

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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

GREECE
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Rafael Sebastian

Full Professor

University of Valencia

SPAIN
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Maxime Sermesant

-

FRANCE
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Esther Pueyo

Universidad de Zaragoza

SPAIN
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Oscar Camara

Full Professor

Universitat Pompeu Fabra

SPAIN
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George Kagadis

Professor of Medical Physics - Medical Informatics

University of Patras

GREECE
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Julien Bert

Research Scientist, head of the research group: Dose optimisation for image guided therapy

University of Brest

FRANCE
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