Related Experiment Video
Updated: Sep 5, 2025
Blood Flow Imaging with Ultrafast Doppler
Published on: October 14, 2020
Optimally filtering and matching processing for regional upstrokes to improve ultrasound transit time-based local PWV
Hong Mo1, Xun Lang1, Yufeng Zhang1
1Department of Electronic Engineering, Information School, Yunnan University, Kunming, Yunnan, 650091, China.
Background And Objective:
Pulse wave velocity (PWV) is an important index for quantifying the elasticity of artery. Local PWV estimates based on ultrasonic transit time (TT) methods, however, are affected by the reflected waves and ultrasonic noise, biasing the spatiotemporal propagation of the time fiduciary point (TFP) positioning in the distension waveforms. In this study, an optimally filtering and matching processing for regional upstrokes is proposed to improve the ultrasound TT-based local PWV estimation.
Method:
(i) Smooth the pulse waves (PWs) using the Savitzky-Golay filter with one set of randomly combined parameters. (ii) An arbitrary region at the first beam upstroke of the smoothed PWs is selected as the curve template, and then matched with the upstrokes of other PWs by calculating the sum of square differences (SSD) between the template and matching regions to find its similar regions. (iii) Update the filter parameters and the template using the moth-flame optimization (MFO) feedback for computing the new SSD value. When the new SSD value is smaller than the historical one, the later will be replaced. (iv) Repeat the above steps until the MFO algorithm converges to the minimum SSD value. (v) Output the optimal filter parameters and the locations of regional curves corresponding to the minimum SSD value. Then the time delay of the PWs propagation can be detected by using the starting points of the regional curves as the TFPs.
Results:
We conducted performance comparison with the advanced TT method through both simulation and clinical experiments. The results demonstrate that the proposed work observes considerable reductions on both the normalized root mean square error ± the standard deviation (from 6.73 ± 2.27% to 1.57 ± 0.72%) and the coefficient of variation (from 13.39% to 8.87%).
Conclusions:
The results of this study support that the proposed method may facilitate the early diagnosis and prevention of local arterial stiffness .
