Forward-backward minimum variance beamforming combined with coherence weighting applied to ultrasound imaging

摘要

Currently, the delay-and-sum (DAS) algorithm is used as a standard technique in ultrasound beamforming. The adaptive ultrasound beamformer, however, shows its superiority over the traditional beamformer, DAS, in many ways. In this paper, we proposed a novel adaptive beamformer which combined the minimum variance (MV) adaptive beamformer together with coherence weighting factor (CF) and forward-backward averaging (FB) to medical ultrasound imaging. We called it the forward-backward averaging coherence weighting minimum variance (FB-CF-MV) beamformer. Based on SonixRP system, we built an ultrasound beamforming research platform. We used this open platform to collect pre-beamforming RF data, and then processed them in Matlab. We tested our algorithm on a fetal ultrasound phantom and compared it with DAS and MV algorithm. The results showed that the new beamformer improved image contrast, making the image outline smoother while compared with other two algorithms.