Study And Experiment On Adaptive Beamforming Algorithm For Ultrasound Imaging

Ultrasound imaging has been widely used in clinical and industrial diagnosis for its safety, convenient, real time and low cost. Although the ultrasound imaging technique has its own advantages, it still has many problems need to solve when it compares to the Magnetic Resonance Imaging(MRI), CT and the X-ray imaging techniques. For example, the resolution of the image is low and suffers from the noises, meantime, its frame rate is unsatisfactory. With the demand of ultrasound imaging, the requirement of its image quality is higher.The performance of beamfoming ability play a core role in ultrasound imaging, it would influence the image quality directly. Generally, the main lobe width and the side lobe level are often adopted as the index to measure the performance of beamfoming ability, the contrast ratio(CR) is another indictor for ultrasound imaging. The narrower the main lobe width is, the resolution is better, and the lower the side lobe level is, the contrast ratio is higher. The contrast to noise ratio is the proxy for robustness of algorithm, the smaller the better. Traditional delay and sum(DAS) beamforming has the feature of quick imaging, but it performs badly in the main lobe width, the side lobe level and the contrast ratio aspect. With the introduction of apodization and dynamic focus, the contrast ratio is improved to some degree with the cost of sacrificing the resolution. The minimum variance(MV) is the most adopted adaptive beamforming technique. Though it can improve the resolution of the image, it has no contribution to the contrast ratio improving to the image and is subject to the steering vector. At the same time, its robustness against the noises is degraded. As to the problems of apodization and the minimum variance, this dissertation investigates the application of the improved adaptive beamforming technique for ultrasound imaging:(1) The improved minimum variance algorithm in ultrasound imaging system(IMV) is proposed. The received signal was divided into desired signal and noise signal at first, then the adaptive weighting vectors were obtained by minimizing the output power of the desired signal. In addition, a pair of constrained conditions were added to the steering vector to further enhance the robustness ability against the noise.(2) The improved generalized side lobe canceller beamforming method for ultrasound imaging(IGSC) is proposed. Firstly, weighting vector is divided into adaptive and non-adaptive two parts. Then the non-adaptive part is projected into the signal space, which is constructed by the covariance matrix of receive data, to obtain a new steer vector. Subsequently, generate the blocking matrix based on the orthogonal complementary space of the new steer vector and update the weighting vector at last.In the end, the simulation is conducted to verify the effectiveness of the proposed method. Furthermore, our lab has developed the ultrasound imaging platform to conduct the experiment, also the data offered by the Michigan University is also adopted to validate the proposed method superiority in improving the resolution, contrast ratio, and the robustness against the noise.