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使用基于特征空间的稳健 Capon 波束形成器对超声治疗中的空化进行被动声学测绘。

Passive acoustic mapping of cavitation using eigenspace-based robust Capon beamformer in ultrasound therapy.

机构信息

The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, People's Republic of China.

The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, People's Republic of China.

出版信息

Ultrason Sonochem. 2018 Mar;41:670-679. doi: 10.1016/j.ultsonch.2017.10.017. Epub 2017 Oct 20.

Abstract

Pulse-echo imaging technique can only play a role when high intensity focused ultrasound (HIFU) is turned off due to the interference between the primary HIFU signal and the transmission pulse. Passive acoustic mapping (PAM) has been proposed as a tool for true real-time monitoring of HIFU therapy. However, the most-used PAM algorithm based on time exposure acoustic (TEA) limits the quality of cavitation image. Recently, robust Capon beamformer (RCB) has been used in PAM to provide improved resolution and reduced artifacts over TEA-based PAM, but the presented results have not been satisfactory. In the present study, we applied an eigenspace-based RCB (EISRCB) method to further improve the PAM image quality. The optimal weighting vector of the proposed method was found by projecting the RCB weighting vector onto the desired vector subspace constructed from the eigenstructure of the covariance matrix. The performance of the proposed PAM was validated by both simulations and in vitro histotripsy experiments. The results suggested that the proposed PAM significantly outperformed the conventionally used TEA and RCB-based PAM. The comparison results between pulse-echo images of the residual bubbles and cavitation images showed the potential of our proposed PAM in accurate localization of cavitation activity during HIFU therapy.

摘要

脉冲回波成象技术只能在高强度聚焦超声(HIFU)关闭时发挥作用,因为主 HIFU 信号与传输脉冲之间存在干扰。被动声成象(PAM)已被提出作为 HIFU 治疗的真正实时监测工具。然而,最常用的基于时间暴露声(TEA)的 PAM 算法限制了声空化图象的质量。最近,稳健的 Capon 波束形成器(RCB)已用于 PAM 中,以提供比基于 TEA 的 PAM 更高的分辨率和更少的伪影,但提出的结果并不令人满意。在本研究中,我们应用了基于特征空间的 RCB(EISRCB)方法来进一步提高 PAM 图象质量。通过将 RCB 加权向量投影到由协方差矩阵特征结构构建的期望向量子空间,找到了所提出方法的最优加权向量。通过模拟和离体组织破碎实验验证了所提出的 PAM 的性能。结果表明,所提出的 PAM 明显优于传统的 TEA 和基于 RCB 的 PAM。残余气泡的脉冲回波图象与空化图象的比较结果表明,我们提出的 PAM 具有在 HIFU 治疗期间准确定位空化活动的潜力。

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