Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
SHR Neuro Krebs Kardio Lipid Stoffw Microb
Costa, CM; Hoetzl, E; Rocha, BM; Prassl, AJ; Plank, G.
Automatic Parameterization Strategy for Cardiac Electrophysiology Simulations.
Comput Cardiol (2010). 2013; 40(2):373-376
[OPEN ACCESS]
PubMed
- Führende Autor*innen der Med Uni Graz
- Mendonca Costa Caroline
- Plank Gernot
- Co-Autor*innen der Med Uni Graz
- Hötzl Elena
- Prassl Anton
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- Abstract:
- Driven by recent advances in medical imaging, image segmentation and numerical techniques, computer models of ventricular electrophysiology account for increasingly finer levels of anatomical and biophysical detail. However, considering the large number of model parameters involved parameterization poses a major challenge. A minimum requirement in combined experimental and modeling studies is to achieve good agreement in activation and repolarization sequences between model and experiment or patient data. In this study, we propose basic techniques which aid in determining bidomain parameters to match activation sequences. An iterative parameterization algorithm is implemented which determines appropriate bulk conductivities which yield prescribed velocities. In addition, a method is proposed for splitting the computed bulk conductivities into individual bidomain conductivities by prescribing anisotropy ratios.