Research On Peak Jump Point Analysis In Ultrasonic Speckle Motion Trackin

Ultrasound speckle motion tracking technology is a key step in many medical ultrasound imaging technologies(such as ultrasound elastography,blood flow imaging,etc.)and has always been the focus of researchers.In the ultrasonic radio frequency signal,the movement of ultrasonic speckle essentially represents the movement of each voxel,so speckle tracking technology can be used to estimate the movement displacement of each position in the tissue.Due to the de-correlated factors such as the electronic noise introduced by the ultrasound equipment’s own acquisition signal,the movement of the human body tissue and the large deformation caused by the squeezing of the probe have raised the accuracy of the ultrasonic speckle motion tracking technology and the robustness of the algorithm place higher demands.Therefore,how to overcome the above de-correlation factors and further improve the ultrasonic speckle motion tracking technology has been the focus of research in this field.The problem of peak-hopping error is that the ultrasonic motion tracking technology is disturbed by decorrelation factors when calculating the displacement,so that the result of the incorrect correlation peak is obtained.Ultrasonic motion tracking technology uses the obtained RF signal to perform ultrasonic motion tracking.When the echo signal is de-correlated and the amplitude of the random correlation peak exceeds the amplitude of the true correlation peak corresponding to the correct speckle motion,the peak-hopping error is then generated.Regarding the problem of peak-hopping error,the current research mainly focuses on the motion estimation algorithm to reduce the peak-hopping error,such as the area growth algorithm using prior information,Bayesian algorithm and GLUE algorithm using displacement regularization,providing sub-sampling Coupled algorithms such as displacement estimation accuracy,these algorithms are excellent in removing the peak jump point.However,according to the literature,there have been no reports on the study of the statistical law of the spatial distribution of peak-hopping error.The study of the spatial distribution of peak-hopping error will certainly further promote the research of related algorithms.After literature research,it is found that the peak-hopping error is similar to the distribution of galaxy point objects in astronomy.In astronomy,two-point correlation functions are usually used to study the distribution of galaxies.In this article,the correct displacement estimation point and peak-hopping error are regarded as two types.Heterogeneous materials to study tissue displacement estimates may be significantly affected by the spatial distribution of their constituent particles.This paper uses the two-point correlation function method commonly used in astronomy for the first time to analyze and study the statistical law of the spatial distribution of peak-hopping error.At the same time,a variety of peak-hopping error removal algorithms are implemented and compared and analyzed.The main research contents are as follows:1.Analysis of the two-point correlation function of the peak transition point.Because the cause of the peak-hopping error is different from that of ordinary image noise,in order to obtain better displacement estimation accuracy,the kernel window size,tissue material,and model of the displacement estimation algorithm are discussed in this paper.Complexity,probe parameters,compression ratio,and other factors have been studied.It is found that the rules of the peak-hopping error are different under the influence of these factors.In order to analyze the rules of these peak-hopping error,this article first refers to two points in astronomy.The correlation function analyzes the peak-hopping error under the influence of different factors,and obtains the peak-hopping error under the influence of each factor and the best parameters for ultrasonic speckle motion tracking.2.Implementation and comparative study of peak-hopping error removal algorithms.This paper implements several existing peak-hopping error removal algorithms and uses computer digital phantoms for experimental verification,and conducts comparative research on related evaluation indicators.Based on the analysis of the conclusions of the peak-hopping error obtained in this paper,a better peak-hopping error removal scheme is found.Under the influence of tissue materials and the peak-hopping error of plaque radius≤10,the elastic strain map obtained by NCC&med algorithm is more accurate;when the plaque radius ≥10,the elastic strain map obtained by RGBMT algorithm is more accurate.The advantages and disadvantages of other algorithms under the influence of various factors are also better reflected in this article.These research results can provide some reference for future peak-hopping error research and algorithm improvement.