东北大学学报(自然科学版) ›› 2021, Vol. 42 ›› Issue (7): 960-965.DOI: 10.12068/j.issn.1005-3026.2021.07.008

• 信息与控制 • 上一篇    下一篇

基于加权因子的双重延时乘累加波束形成算法

鲍喜荣, 历正双, 高浩森, 张石   

  1. (东北大学 计算机科学与工程学院, 辽宁 沈阳110169)
  • 修回日期:2020-10-10 接受日期:2020-10-10 发布日期:2021-07-16
  • 通讯作者: 鲍喜荣
  • 作者简介:鲍喜荣(1978- ),男,湖北当阳人,东北大学讲师,博士; 张石(1963- ),男,辽宁抚顺人,东北大学教授,博士生导师.
  • 基金资助:
    中央高校基本科研业务费专项资金资助项目(N171604011).

Double Delay Multiplication and Accumulation Beamforming Algorithm Based on Weighting Factor

BAO Xi-rong, LI Zheng-shuang, GAO Hao-sen, ZHANG Shi   

  1. School of Computer Science & Engineering, Northeastern University, Shenyang 110169, China.
  • Revised:2020-10-10 Accepted:2020-10-10 Published:2021-07-16
  • Contact: LI Zheng-shuang
  • About author:-
  • Supported by:
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摘要: 针对超声成像中双重延时乘累加算法不适用于高噪声环境的问题,提出一种基于均值-标准差加权因子的双重延时乘累加算法,即RD-DMAS算法.该加权因子对解决高噪声带来的图像斑点问题具有显著效果,而双重延时乘累加波束形成算法能大幅提高超声成像分辨率,使所提算法能得到高分辨率和高对比度的重建图像.对该算法在点散射目标仿体、囊肿仿体和噪声环境下进行了仿真,结果表明,RD-DMAS算法有最小旁瓣以及较窄的主瓣.DAS,DMAS,DS-DMAS,RD-DMAS算法的对比度(CR)分别为9.72,11.72,13.28和19.86.不管环境中是否有噪声,RD-DMAS算法的成像效果都是最好的.

关键词: 波束形成算法;加权因子;延时乘累加;超声成像;重建图像

Abstract: In order to solve the problem that the double delay multiplication and accumulation algorithm in ultrasonic imaging is not suitable for high noise environments, a double delay multiplication and accumulation algorithm based on mean-standard deviation weighting factor, namely RD-DMAS algorithm, is proposed. The weighted factor has a significant effects on solving the image speckle problem caused by strong noises, and the dual delay multiplication and accumulation beamforming algorithm can greatly improve the resolution of ultrasonic imaging, so the new method can obtain high resolution and high contrast image reconstruction. The algorithm was simulated in point scattering target replicas, cyst replicas and noise environments, and the results show that the RD-DMAS has the smallest sidelobe and narrower main lobe. The contrast ratios(CR)of DAS, DMAS, DS-DMAS and RD-DMAS were 9.72, 11.72, 13.28 and 19.86, respectively. RD-DMAS provides the best imaging performance regardless of noise in the environment.

Key words: beamforming algorithm; weighting factor; delay multiplication and accumulation; ultrasonic imaging; image reconstruction

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