# Shear Wave Velocity Estimation Using the Real-Time Curve Tracing Method in Ultrasound Elastography
## 5 Discussion  
In the homogeneous region with an elastic modulus of 30 kPa, the estimated velocity, the standard deviation and the relative error with the time-to-peak method are 2.8078 m/s, 0.1944 m/s and 11.21%, respectively. The corresponding estimated values of the lateral peak method are 2.8622 m/s, 0.2114 m/s and 9.49%. However, the estimated velocity, the standard deviation and the relative error with the real-time curve tracing method are 2.9382 m/s, 0.1221 m/s and 7.09%, respectively. Evidently, compared to the time-to-peak method and the lateral peak method, the real-time curve tracing method improves the accuracy while estimating the shear wave velocity in the homogeneous area, which is due to the improved frame rate stability of hardware devices. The main factor affecting the accuracy of the real-time curve tracing method is the stability of the frame rate. If the frame rate stability is evaluated and modified, the accuracy of shear wave velocity estimation will be further improved. The experimental results show that the real-time curve tracing method can provide new ideas for the evaluation of shear wave velocity and elastic parameters.  
It can be concluded from the experimental results of the homogeneous region of the 040 GSE ultrasound phantom that the real-time curve tracing method has more advantages in image reconstruction of shear wave velocity because of its high accuracy in two-dimensional shear wave velocity estimation. In the results obtained by using the stiff spherical inclusion regions, the results fully illustrate that for the stiff spherical inclusion regions, regardless of the elasticity and location of inclusions, the shear wave velocity image can be reconstructed by using the real-time curve tracing method. The above experimental results verify the feasibility of the real-time curve tracing method for shear wave velocity image reconstruction in the stiff spherical inclusion regions.  
In the noise experiment, the experimental results show that the influence of Gaussian noise on velocity estimation is small, which indicates that this method has strong noise adaptability. Since the time-to-peak method and the lateral peak method use peak data to calculate shear wave velocity, and peak value is easily affected by noise, the real-time curve tracing method has better anti-noise performance than the time-to-peak method and the lateral peak method.  
In recent years, most methods are based on time domain data to estimate shear wave velocity. These methods estimate shear wave velocity by the characteristics of shear wave motion [34, 35]. Among them, when the time signal cross-correlation is used to calculate the shear wave velocity [36], the size of the window will affect the measurement results of shear wave velocity. However, the proposed real-time curve tracing method avoids the influence of window size on shear wave estimation velocity by image processing technology.  
At present, there are some methods to estimate shear wave velocity using frequency domain data, which are common methods proposed in recent years [37, 38, 39]. Most of these estimation methods have limited spatial range in the transverse and longitudinal directions. In order to change this defect, many research teams have extended these methods, such as making them generate images of phase velocity or viscoelastic characteristics [40, 41]. In 2018, [PERSON] and [PERSON] proposed local phase velocity imaging to create phase velocity images at different frequencies in homogeneous and heterogeneous media using Fourier decomposition and moving windows [38]. One of the limitations of the local phase velocity imaging method is that the results may be corrupted by outliers or motion records with high noise content. However, the real-time curve tracing method can avoid outliers in image filtering.