Abstract
Fiber orientation is a major factor in the determination of end-systolic strains within models of cardiac mechanics. Unfortunately, direct patient-specific acquisition of fiber orientation is not readily available nowadays in the clinic. As an alternative, we propose to use the Reduced Order Unscented Kalman Filter to estimate rule-based fiber orientation parameters from end-systolic wall strains that can be obtained using more traditional imaging methodologies. We address the estimation of fiber orientation in the physiological left ventricle, where end-systolic strains were generated in-silico using a 12-parameter rule-based fiber model. The estimation process focused on the determination of the three most influential parameters of an imperfect 5-parameter rule-based fiber model. Our results show that these three fiber parameters can be estimated within an average deviation of 6\(^{\circ }\) from a combination of three end-systolic strains even when the initial guess for each estimated parameter was set 10\(^{\circ }\) away from the ground truth value.
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Barbarotta, L., Bovendeerd, P.H.M. (2021). Parameter Estimation in a Rule-Based Fiber Orientation Model from End Systolic Strains Using the Reduced Order Unscented Kalman Filter. In: Ennis, D.B., Perotti, L.E., Wang, V.Y. (eds) Functional Imaging and Modeling of the Heart. FIMH 2021. Lecture Notes in Computer Science(), vol 12738. Springer, Cham. https://doi.org/10.1007/978-3-030-78710-3_33
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DOI: https://doi.org/10.1007/978-3-030-78710-3_33
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