A beamforming algorithm with composite multi-conditional cross correlation and range standard deviation factor for high quality ultrasound imaging

The traditional delay-and-sum (DAS) beamformer is inadequate for clutter suppression in ultrasound imaging. The coherence factor beamformer can effectively suppress clutter, but it is prone to cause dark-region artifacts during incoherent signal suppression. In this paper, the resolution and contrast of ultrasound images are improved by using a novel adaptive beamforming algorithm called composite multi-conditional cross correlation (MCC) and range standard deviation factor (CMCC-RSF). The MCC algorithm is obtained by integrating the conditional coherence and cross correlation factor, which can better balance clutter suppression ability inside the anechoic cyst and speckle background quality. Then, we propose a range standard deviation factor (RSF) to improve the resolution of MCC without destroying the speckle background. The simulation and experiment results show that compared with traditional DAS, the full-width at half-maximum of CMCC-RSF is improved by 75.14%, 47.62%, 49.27%, and 55.97%, respectively. According to the experiment results, the contrast ratio and speckle signal-to-noise ratio of CMCC-RSF are maximally improved by 154.38%, and 124.53%, respectively. In general, the proposed CMCC-RSF algorithm can improve comprehensive image quality with low relative computational complexity.