Impact of uncertainties in cardiac mechanics simulations
Abstract
The heart simulations have a high potential for use in diagnosis and therapy planning. However, such clinical use puts strict demands on the reliability of the model predictions due to errors and uncertainty in the model inputs. The model parameters are difficult to be measured and they are associated with considerable uncertainty. Furthermore, patient-specific geometries are generated from medical images involving semi-manual processing, which becomes a potential source of uncertainty. In order to contribute to the reliability assessment of cardiac mechanics models, in this study we apply uncertainty quantification and sensitivity analysis for finite element simulations of the left ventricle during the cardiac cycle.
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