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基于连续小波变换的爬行波声弹性成像的剪切波速度估算。

Shear Wave Speed estimator using Continuous Wavelet Transform for Crawling Wave Sonoelastography.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:3994-3997. doi: 10.1109/EMBC46164.2021.9629702.

Abstract

Crawling Wave Sonoelastography (CWS) is an elastography ultrasound-based imaging approach that provides tissue stiffness information through the calculation of Shear Wave Speed (SWS). Many SWS estimators have been developed; however, they report important limitations such as the presence of artifacts, border effects or high computational cost. In addition, these techniques require a moving interference pattern which could be challenging for in vivo applications. In this study, a new estimator based on the Continuous Wavelet Transform (CWT) is proposed. This allows the generation of a SWS image for every sonoelasticity video frame. Testing was made with data acquired from experiments conducted on a gelatin phantom with a circular inclusion. It was excited with two vibration sources placed at both sides with frequencies ranging from 200 Hz to 360 Hz in steps of 20 Hz. Results show small variation of the SWS image across time. Additionally, images were compared with the Phase Derivative method (PD) and the Regularized Wavelength Average Velocity Estimator (R-WAVE). Similar SWS values were obtained for the three estimators within a certain region of interest in the inclusion (At 360 Hz, CWT: 5.01±0.2m/s, PD: 5.11±0.28m/s, R-WAVE: 4.51±0.62m/s) and in the background (At 360 Hz, CWT: 3.67±0.15m/s, PD: 3.69±0.23m/s, R-WAVE: 3.58±0.24m/s). CWT also presented the lowest coefficient of variation and the highest contrast-to-noise ratio for most frequencies, which allows better discrimination between regions.Clinical relevance-This study presents a new Shear Wave Speed estimator for Crawling Wave Sonoelastography, which can be useful to characterize soft tissue and detect lesions.

摘要

爬波声弹性成像(Crawling Wave Sonoelastography,CWS)是一种基于超声的弹性成像方法,通过计算剪切波速度(Shear Wave Speed,SWS)来提供组织硬度信息。已经开发了许多 SWS 估计器,但是它们报告了重要的限制,例如存在伪影、边界效应或高计算成本。此外,这些技术需要一个移动的干扰模式,这对于体内应用可能具有挑战性。在这项研究中,提出了一种基于连续小波变换(Continuous Wavelet Transform,CWT)的新估计器。这允许为每个声弹性视频帧生成一个 SWS 图像。测试是使用在具有圆形包含物的明胶仿体上进行的实验获得的数据进行的。它使用放置在两侧的两个振动源以 20 Hz 的步长从 200 Hz 到 360 Hz 的频率进行激励。结果表明,SWS 图像随时间的变化很小。此外,将图像与相位导数方法(Phase Derivative method,PD)和正则化波长平均速度估计器(Regularized Wavelength Average Velocity Estimator,R-WAVE)进行了比较。在包含物内的某个感兴趣区域(在 360 Hz 时,CWT:5.01±0.2m/s,PD:5.11±0.28m/s,R-WAVE:4.51±0.62m/s)和背景(在 360 Hz 时,CWT:3.67±0.15m/s,PD:3.69±0.23m/s,R-WAVE:3.58±0.24m/s)中,三个估计器获得了相似的 SWS 值。CWT 还在大多数频率下表现出最低的变异系数和最高的对比度噪声比,这允许更好地区分区域。临床意义-本研究提出了一种用于爬波声弹性成像的新的剪切波速度估计器,它可以用于表征软组织和检测病变。

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