融合最小方差自适应和相干系数波束合成的超快速主动空化成像方法

基于平面波发射和延迟叠加(DAS)波束合成的超高速主动空化成像能够以高帧频监测超声空化活动, 但其图像分辨率和对比度较低. 本文提出一种结合最小方差自适应算法(MV)和相干系数算法(CF)实现基于MVCF波束合成的超高速主动空化成像, 以此提高空化图像质量. 通过Field II仿真和实验数据全面详细验证本方法的有效性与优点, 仿真数据包括点目标和囊肿仿体, 实验数据是对1.2 MHz单聚焦超声换能器产生的空化泡采集原始射频数据. 文中将MVCF波束合成算法与传统B超图像、 DAS、 MV、 DAS-CF和MVCS波束合成算法进行比较. 结果表明, 基于MVCF波束合成的超高速主动空化成像可显著提高空化图像的信噪比和分辨率. 与传统B超图像相比, 基于MVCF波束合成的超高速主动空化成像图像信噪比高21.82 dB, 且横向和轴向空间分辨率分别是传统B超图像的2.69倍和1.93倍. 基于MVCF波束合成的超高速主动空化成像能够以较高的信噪比和分辨率监测超声空化活动.

Minimum variance adaptive beamforming combined with coherence factor weighting applied to ultrafast active cavitation imaging

The ultrafast active cavitation imaging (UACI) based on plane wave transmission and delay-and-sum (DAS) beamforming has been developed to monitor cavitation events with a high frame rate. However, DAS beamforming leads to images with limited resolution and contrast. In this paper, minimum variance (MV) adaptive beamforming and coherence factor (CF) weighting are combined to achieve an MVCF-based UACI, which can improve the cavitation imaging quality. The detailed algorithm evaluation has been investigated from both simulation and experimental data. The simulation data include 10 point targets and a cyst, while the experimental data are obtained by detecting the dissipation of cavitation bubbles in water excited by a single element transducer with frequency of 1.2 MHz. The advantages of the proposed methodology as well as the comparison with conventional B-mode, DAS, MV, DAS-CF and MV on the basis of compressive sensing (CS) (called MVCS) beamformers are discussed. The results show that MVCF beamformer has a significant improvement in terms of both resolutions and signal-to-noise ratio (SNR).The MVCF-based UACI has a SNR at 21.82 dB higher, lateral and axial resolution at 2.69 times and 1.93 times, respectively, which were compared with those of B-mode active cavitation mapping. The MVCF-based UACI can be used to image the residual cavitation bubbles with a higher SNR and better spatial resolution.