Restoration Of Echocardiograms Using Time Warping And Periodic Averaging On A Normalized Time Scale

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Abstract
This paper describes an algorithm for the restoration of echocardiographic sequences of several consecutive heart beats. It is based on the estimation of the parameters of a quasi-periodic signal model. This model is fully characterized by a one-period-long reference signal and a warping function that defines the mapping between the reference and observed time-scales. Given an initial reference template, an optimal warping function is determined using dynamic programming. This function is optimal in the sense that it minimizes the mean square error between the warped template and the measured noisy signal. A reference signal estimate is then formed by averaging several cardiac cycles with reference to a normalized time-scale. The efficiency of this procedure, which may be iterated, is demonstrated quantitatively using quasi-periodic noisy test data. This method is then applied to the improvement of M-mode echocardiograms.

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