A new parametric autoregressive spectral approach using Burg and Yule Walker algorithms successfully evaluated arterial wall deformations in a tube phantom and in vitro carotid tissue.
Does a high-resolution spectral approach improve the evaluation of arterial wall deformations compared to a classical cross-correlation operator in a tube phantom and in vitro carotid tissue?
A new high-resolution spectral approach using parametric autoregressive processing offers a potential alternative to classical cross-correlation methods for evaluating arterial wall deformations.
By locally measuring changes on arterial wall thickness as a function of pressure, the related Young modulus can be evaluated. This physical magnitude has shown to be an important predictive factor for cardiovascular diseases. For evaluating those changes, imaging segmentation or time correlations of ultrasonic echoes, coming from wall interfaces, are usually employed. In this paper, an alternative low-cost technique is proposed to locally evaluate variations on arterial walls, which are dynamically measured with an improved high-resolution calculation of power spectral densities in echo-traces of the wall interfaces, by using a parametric autoregressive processing. Certain wall deformations are finely detected by evaluating the echoes overtones peaks with power spectral estimations that implement Burg and Yule Walker algorithms. Results of this spectral approach are compared with a classical cross-correlation operator, in a tube phantom and "in vitro" carotid tissue. A circulating loop, mimicking heart periods and blood pressure changes, is employed to dynamically inspect each sample with a broadband ultrasonic probe, acquiring multiple A-Scans which are windowed to isolate echo-traces packets coming from distinct walls. Then the new technique and cross-correlation operator are applied to evaluate changing parietal deformations from the detection of displacements registered on the wall faces under periodic regime.
Bazán et al. (Wed,) conducted a other in Cardiovascular diseases. High-resolution calculation of power spectral densities (Burg and Yule Walker algorithms) vs. Classical cross-correlation operator was evaluated on Changing parietal deformations (displacements registered on the wall faces). A new parametric autoregressive spectral approach using Burg and Yule Walker algorithms successfully evaluated arterial wall deformations in a tube phantom and in vitro carotid tissue.
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