Time-resolved cardiac CT reconstruction using a nonlinear Kalman-Filter based algorithm

We propose an algorithm to solve the problem of time-resolved cardiac computed tomography (CT). The goal of the algorithm is to reconstruct a snapshot of the moving heart at any time instant from CT projection data acquired over a single heart-cycle. The object is modeled by a spatio-temporal state-space model which requires a nonlinear version of the Kalman Filter to assimilate the sequentially acquired projection data. Simulation results show that the nonlinear model overcomes shortcomings of the previously used linear model.