摘要
为了提高空化图像的质量,该文提出一种结合空化微泡母小波技术(CBWT)、波束合成和平方差值求和减影(SSD)的超快速主动空化成像方法。该方法首先发射平面波并接收空化回波信号;其次,基于RPNNP模型构建空化微泡母小波,对空化回波信号进行连续小波变换;再次,对获得的小波系数进行波束合成,包括延迟叠加算法(DAS)、最小方差算法(MV)和相干系数最小方差算法(MVCF),再结合SSD,得到空化图像。结果表明,与未采用CBWT相比,基于CBWT-DAS-SSD、CBWT-MV-SSD和CBWT-MVCF-SSD的空化噪声比分别提高了16.34 dB、15.07 dB、17.71 dB。该方法可提高空化成像质量,为空化动态实时监控提供参考。
In order to improve the quality of cavitation image,in this paper,an ultrafast active cavitation imaging combined cavitation bubble wavelet(CBWT),beamform algorithm and sum-of-squared differences(SSD)algorithm is proposed.Firstly,plane wave pulse is transmited and cavitation echo signal is received.Secondly,based on RPNNP model,the cavitation bubble mother wavelet is constructed and continuous wavelet transform is performed on cavitation echo signal.Thirdly,the obtained wavelet coefficients are beformed by delay-and-sum algorithm(DAS),minimum-variance algorithm(MV)and coherence coefficient minimum variance algorithm(MVCF).Furthermore,SSD algorithm is used to obtain the cavitation image.The results show that compared with cavitation images without CBWT,the cavitation-to-noise ratios of cavitation images based on CBWT-DAS-SSD,CBWT-MV-SSD and CBWT-MVCF-SSD increased by 16.34 dB,15.07 dB and 17.71 dB,respectively.The method in this paper can improve the quality of cavitation image,and may provide reference for dynamic real-time monitoring of cavitation bubbles.
作者
田淑爱
丁婷
田志鑫
杨录
TIAN Shu’ai;DING Ting;TIAN Zhixin;YANG Lu(Shanxi Provincial Key Laboratory of“Biomedical Imaging and Imaging Big Data”,North University of China,Taiyuan 030051,China)
出处
《应用声学》
CSCD
北大核心
2020年第6期849-856,共8页
Journal of Applied Acoustics
基金
国家自然科学基金青年科学基金项目(11604305)
山西省自然科学面上青年基金项目(201901D211232)。
关键词
超快速超声空化成像
微泡母小波技术
波束合成算法
数字减影
Ultrafast active cavitation imaging
Cavitation bubble wavelet transform
Beamform algorithm
Digital subtraction
