信噪比后滤波与特征空间融合的最小方差超声成像算法  

Signal to noise ratio dependent postfilter combined with eigenspace-based minimum variance algorithm for ultrasound imaging

作　　者：王平[1] 江金洋 李昉 林楠 岳影 WANG Ping;JIANG Jinyang;LI Fang;LIN Nan;YUE Ying(State Key Lab.of Power Transmission Equip.& System Secumty and New Tech., Chongqing Universzty Chongqing 400044;East Inner Mongolia Electric Power Limited Company Hohhot 010020)

机构地区：[1]重庆大学输配电装备及系统安全与新技术国家重点实验室,重庆400044 [2]国网内蒙古东部电力有限公司检修分公司,内蒙古010020

出　　处：《声学学报》2019年第1期136-144,共9页Acta Acustica

基　　金：国家自然科学基金项目(51677010);重庆市研究生科研创新项目(CYS16029);重庆市科技计划项目(cstc2016jcyjA29 13)资助

摘　　要：为了提高超声成像空间分辨率和对比度,提出了一种信噪比后滤波与特征空间融合的最小方差波束形成算法。首先,利用信号子空间划分将最小方差算法得到的权矢量投影到信号子空间中提高成像对比度,然后基于信号相干性设计滤波系数,并引入基于信噪比的噪声加权系数,最终得到融合信噪比后滤波与特征空间的最小方差算法。为验证本算法的有效性,使用FieldⅡ对点目标和吸声斑目标进行了仿真实验验证,并采用密歇根大学geabr_0实验数据进行成像。实验结果表明:所提算法在对比度和分辨率上均有所提高,明显优于传统延时叠加算法,最小方差算法和ESBMV_wiener算法,且对噪声具有较强鲁棒性。In order to improve the spatial resolution and contrast of ultrasound imaging, a signal to noise ratio-based postfilter hybrid eigenspace-based minimum variance algorithm is proposed. Firstly, the subspace dividing of signal is used to improve the contrast of the minimum variance method by projecting the weight vector of it into the signal subspace. Then, the factor of postfilter is calculated by the coherence of the signal, and a noise weighting factor based on signal to noise ratio is introduced. Finally, a signal to noise ratio-based postfilter combined with eigenspace-based minimum variance algorithm is obtained. In order to validate the proposed algorithm, we used FieldⅡ to simulate point target and the cyst phantom, and the experimental data of geabr_0 proposed by Michigan University was also used to imaging. Experiment results indicate that both the contrast and resolution are improved by the algorithm proposed,and the performance index is obviously superior to the traditional delay and sum method, minimum variance algorithm and the ESBMVwiener algorithm, and the algorithm is robust to noise.

关 键 词：成像算法 最小方差 滤波系数 特征空间 空间融合 超声成像 信噪比 信号子空间 

分 类 号：O426.9[理学—声学]