Page 55 - 《应用声学》2020年第6期
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第 39 卷 第 6 期                                                                       Vol. 39, No. 6
             2020 年 11 月                         Journal of Applied Acoustics                 November, 2020

             ⋄ 研究报告 ⋄



               结合空化微泡母小波变换的高空化噪声比超快速


                                          主动空化成像方法                           ∗



                                         田淑爱 丁 婷           †   田志鑫 杨 录


                                  (中北大学    “生物医学成像与影像大数据” 山西省重点实验室            太原   030051)

                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。
                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
                中图法分类号: R445.1          文献标识码: A          文章编号: 1000-310X(2020)06-0849-08
                DOI: 10.11684/j.issn.1000-310X.2020.06.007



                  An ultrafast active cavitation imaging with high cavitation-to-noise ratio
                                  based on cavitation bubble wavelet transform


                                    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)

                 Abstract: 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.
                 Keywords: Ultrafast active cavitation imaging; Cavitation bubble wavelet transform; Beamform algorithm;
                 Digital subtraction


             2020-06-26 收稿; 2020-09-11 定稿
             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)
             ∗
             作者简介: 田淑爱 (1995– ), 女, 河北沧州人, 硕士研究生, 研究方向: 超声空化成像。
             † 通信作者 E-mail: dting@nuc.edu.cn
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