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.
The traditional minimum variance(MV)adaptive beamforming algorithm for medical ultrasound has the disadvantages of poor robustness,lim ited image contrast enhancement and high algorithm com plexity.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 w ith 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 com plexity is far lower than SFMV.
作者
鲍喜荣
李玉珍
苏婷
张石
BAO Xi-rong;LI Yu-zhen;SU Ting;ZHANG Shi(School of Computer Science&Engineering,Northeastern University,Shenyang 110169,China)
出处
《东北大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2018年第4期468-472,482,共6页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金青年基金资助项目(61302012)
关键词
最小方差
符号相干系数
QR分解
分辨率
对比度
minimum variance(MV)
sign coherence factor(SCF)
QR decomposition
resolution
contrast