医疗超声成像自适应波束形成算法

摘要 针对传统医疗超声最小方差自适应波束形成算法的稳健性差、图像对比度提高有限、算法复杂度高等缺点，在基于QR分解的最小方差(QRMV)波束形成的基础上，引入了符号相干系数，提出了一种基于QR分解的最小方差与符号相干系数融合的自适应波束形成算法.仿真结果表明:该算法分辨率、对比度都优于传统的延时叠加、最小方差及基于QR分解的最小方差算法，表现出和最小方差与符号相干系数融合(SFMV)算法非常接近的性能，但运算复杂度却远低于它.
Abstract：The traditional minimum variance(MV)adaptive beamforming algorithm for medical ultrasound has the disadvantages of poor robustness， limited image contrast enhancement and high algorithm complexity. So， according to the minimum variance beamforming based on QR decomposition(QRMV)， the sign coherence factor was introduced， and an adaptive beamforming algorithm of QRMV combined with sign coherence factor was proposed. The simulation results showed that the proposed algorithm in the aspects of resolution and contrast is superior to the conventional delay and sum(DAS)， MV and QRMV， and its performances are very close to SFMV， but its computational complexity is far lower than SFMV.