Personalization of Cardiac Fiber Orientations from Image Data Using the Unscented Kalman Filter

نویسندگان

  • Andreas Nagler
  • Cristóbal Bertoglio
  • Michael W. Gee
  • Wolfgang A. Wall
چکیده

We propose to estimate rule-based myocardial fiber model (RBM) parameters from DT-MRI, with the goal of personalizing the fiber architecture for cardiac simulations. The RBM is based on a space-dependent angle distribution on the heart surface and then extended to the whole domain through an harmonic lifting of the fiber vectors. For the angles estimation we use a static Unscented Kalman Filter (UKF). We also show the effect of different fiber distributions on cardiac contraction simulations.

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تاریخ انتشار 2013