Study On Beamforming Algorithm Of Ultrasound Imaging

Ultrasound imaging has been widely used in medical applications, such ascardiovascular, abdominal, urinary system, because of its individual characteristics ofhigh safety, real-time, convenience, non-invasion, low cost. The core part of ultrasoundimaging system is beamforming, which directly influence imaging quality. In thetraditional delay-and-sum beamfoming, dynamic focusing, amplitude apodization anddynamic aperture are considered as the common way to control beam. Dynamicfocusing, amplitude apodization and dynamic aperture improve the imaging quality incertain extent, but the imaging mode of traditional delay-and-sum beamfomingrestricted the further improvement, the reason as follows:â‘ Due to the large storage capacity of focusing delay parameters, it is difficult toachieve high-precision dynamic focusing.â‘¡The weights of apodization are fixed function. After apodization, the sidelobelevel was decreasing while the width of mainlobe was increasing, the lateral resolutionwas become worse.Then, for the two problems, the main research works in this dissertation are asfollows:â‘ Compression method of dynamic focusing delay parameters is proposed.Firstly, delay parameters are decomposed into relative delay parameters of adjacentarray elements and are quantification; and then the initial values and the changelocations of relative delay parameters are stored to achieve the compression storage. Atlast, the storage data in the process of dynamic focusing is decompressed to achievereal-time generation of delay parameters required. Performance analysis shows thismethod significantly reduces the storage of delay parameters.â‘¡Improved adaptive beamforming algorithms are proposed.Considering the existed algorithm has the shortcoming in the aspect of imagingcontrast and robustness, the improved algorithms are proposed, such as Minimumvariance beamforming combined with MV-Based coherence factor applied to medicalultrasound imaging(MV+HRCF) and Eigenspace-based forward-backward minimumvariance beamforming applied to ultrasound imaging(EIBFBMV).MV+HRCF algorithm: First, the coherent sum in coherence factor is replaced bythe output of MV to obtain weighting factor, and then the factor is used to weight the results of minimum variance beamforming. The simulated result indicates that theproposed method in the aspects of resolution and contrast is better than existedalgorithm.EIBFBMV algorithm: First, Forward-backward (FB) spatial averaging, instead ofthe conventional forward-only spatial averaging is used to obtain a more accuratecovariance matrix; and then the calculated optimum weight vector is projected onto asignal subspace constructed from the eigenstructure of the covariance matrix; in the end,the obtained vector and the aperture data are calculated to obtain echo data. Theexperimental results show that the proposed method is less dependent on the choice ofthe amount of diagonal loading and enhances the contrast and robustness while the highresolution of the MV beamforming is retained.