Cardiac Ultrasound Imaging Based On Beamforming

Echocardiography is most widely used in the detection of valve motion and the quantitative measurement of non-invasive cardiac function parameters.In ultrasound imaging,ultrasound beamforming has become an important component of ultrasound imaging as it can effectively increase the lateral resolution of the imaging.For cardiac ultrasound imaging in particular,the poor lateral resolution of the beam from the ultrasound front end has led to limitations in many algorithms.In recent years,adaptive beamforming has emerged,unlike the traditional delayed and sum(DAS),allows the lateral resolution of the formed beam to be greatly increased by adaptive calculation of the weight vector of the input echo signal.However,the cost of increased lateral resolution in adaptive beamforming is an increase in imaging time,and the strict requirements for imaging frame rates in cardiac motion pictures have prevented the use of adaptive beamforming in ultrasound equipment.In recent years,with the concept of ultrafast ultrasound imaging being proposed by researchers,plane wave imaging(PWI)has been increasingly used in ultrasound imaging.However,adaptive beamforming methods based on focused wave imaging(FWI)are not suitable for direct application to coherent plane wave compounding(CPWC)due to the severe sidelobe artifacts generated by CPWC and the low signal-to-noise ratio of radio frequency(RF)data acquired from plane waves.In this thesis,three new beamformers are proposed:one is the threshold phase coherence factor(THR-PCF)beamformer,which adaptively adjusts the weight vector by increasing the influence of signals in threshold phase on the weight vector;one is the reconstruction-covariance-matrix minimum variance(RCM-MV)beamformer,which reconstructs the covariance matrix of the array signal on each pixel point according to the value of the eigenvalue,so as to increase the influence of the signal with large eigenvalue on the weight vector and adjust the weight vector adaptively.In order to obtain high-quality images with high resolution and contrast,this paper combines the THR-PCF with RCM-MV and then proposed a novel CPWC-based adaptive beamformer,THR-PCF+RCM-MV.The simulation,phantom,and in-vivo experiments were performed to investigate the performance of the proposed methods in comparison with the CPWC and the classical adaptive methods including the minimum variance(MV),generalized coherence factor(GCF),and their combination GCF+MV.The simulation results demonstrated that the THR-PCF+RCM-MV beamformer improved contrast ratio(CR),contrast noise ratio(CNR)speckle signal-to-noise ratio(s_SNR),generalized contrast-to-noise ratio(GCNR),and the full width at half maximum(FWHM),compared with the GCF+MV method.The phantom experimental results showed a better performance of the THR-PCF+RCM-MV beamformer with an improvement in CR,s_SNR,FWHM compared with the GCF+MV Meanwhile,the results showed that the image quality of the near and far fields was enhanced by the THR-PCF+RCM-MV.The in vivo experiments also validated the imaging results of the simulated and phantom experiments,with improved lateral resolution and contrast in the vascular and cardiac images generated by THR-PCF+RCM-MV beamformers.In order to achieve ultrafast imaging,the proposed THR-PCF,RCM-MV,and THR-PCF+RCM-MV were accelerated by GPU parallel processing,and the imaging speed analysis metrics were calculated,which further reduced the imaging time and lays a good foundation for ultrasound real-time high-definition imaging.