An Inverse Recovery of Cardiac Electrical Propagation from Image Sequences
We present an inverse approach to estimate patient-specific electrical excitations (action potentials) in heart from tomographic medical image sequences in this paper. We first define the geometrical/physical representation of heart, and acquire the dense motion field from image sequences through a stochastic multi-frame motion recovery algorithm. We assume material properties of cardiac muscles are known so that we could calculate the myocardial active forces through the law of force equilibrium from the motion field. Since three dimensional active forces are stimulated by one dimensional active stresses and active stresses are physiologically driven by action potentials, we finally can obtain the pattern of action potentials inside myocardium from active stresses calculated from motion field, where a spatiotemporal regularization with a prior model constraint is applied to estimate action potentials from active forces. We conduct experiments on three dimensional synthetic data and canine magnetic resonance image sequence with favorable results.
KeywordsActive Force Active Stress Tikhonov Regularization Force Equilibrium Move Less Square
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