Robust estimation of Shear Wave group velocity for ultrasound elastography based on frequency domain analysis
Year: 2024
Type: article
Abstract: AIMS: Shear wave elastography (SWE) is of great significance in measuring the elasticity and in evaluating mechanical properties of biological tissues. The elasticity of biological tissues can be reflected by measuring the propagation velocity of shear waves. Therefore, accurate estimation of shear wave velocity is crucial. MATERIAL AND METHODS: In this study, we proposed a robust estimation method based on a cyclic shifting algorithm (CSA) for measuring shear wave group velocity in homogeneous media. To validate the utility of the algorithm, we conducted accuracy analysis and robustness analysis with different noise levels in the digital phantom used for the standardization of shear wave velocity by Quantitative Imaging Biomarker Alliance (QIBA) of the Radiological Society of North America. RESULTS: The estimated shear wave velocities (SWV) of the elastic digital phantoms with Young's moduli 3 kPa, 6 kPa, 15 kPa, 30 kPa are 1.0156 m/s, 1.4065 m/s, 2.1875 m/s, 3.1250 m/s, respectively. When adding Gaussian white noise with 0 dB, the relative errors of the estimated SWVs are 2.5%, 4.8%, 11.8%, 20.5%, respectively. The estimated SWVs in the gelatin phantom with gelatin concentration of 7% and 10% are 2.0442 m/s and 3.1237 m/s. Compared with the existing two representative estimation algorithms, the estimation algorithm proposed in this paper has a higher anti-noise performance due to effective energy accumulation in the frequency domain. CONCLUSIONS: The proposed SWV method based on CSA in frequency domain is a robust shear wave group velocity estimation method, which seems to be a useful tool in homogeneous media for ultrasound elastography.
Source: Medical Ultrasonography
DOI: 10.11152/mu-4464
Authors: Qian Lv, Xin Zhao, Liang Zhao, Ying Liu, Ye Tian, Jianzhong Guo
Institution: Shaanxi Normal University
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
Awards: G3812316298, G5585974953, G7532180977
OpenAlex ID: W4405574209