Therre Sarah, Fournelle Marc, Tretbar Steffen
Department Ultrasound, Fraunhofer Institute for Biomedical Engineering (IBMT), 66280 Sulzbach, Germany.
Department of Molecular and Cellular Biotechnology, Saarland University, 66123 Saarbruecken, Germany.
Sensors (Basel). 2024 Mar 14;24(6):1868. doi: 10.3390/s24061868.
Three-dimensional passive acoustic mapping (PAM) with matrix arrays typically suffers from high demands on the receiving electronics and high computational load. In our study, we investigated, both numerically and experimentally, the influence of matrix array aperture size, element count, and beamforming approaches on defined image metrics. With a numerical Vokurka model, matrix array acquisitions of cavitation signals were simulated. In the experimental part, two 32 × 32 matrix arrays with different pitches and aperture sizes were used. After being reconstructed into 3D cavitation maps, defined metrics were calculated for a quantitative comparison of experimental and numerical data. The numerical results showed that the enlargement of the aperture from 5 to 40 mm resulted in an improvement of the full width at half maximum (FWHM) by factors of 6 and 13 (in lateral and axial dimension, respectively). A larger array sparsity influenced the point spread function (PSF) only slightly, while the grating lobe level (GLL) remained more than 12 dB below the main lobe. These results were successfully experimentally confirmed. To further reduce the GLL caused by array sparsity, we adapted a non-linear filter from optoacoustics for use in PAM. In combination with the delay, multiply, sum, and integrate (DMSAI) algorithm, the GLL was decreased by 20 dB for 64-element reconstructions, resulting in levels that were identical to the fully populated matrix reconstruction levels.
使用矩阵阵列的三维被动声学映射（PAM）通常对接收电子设备有很高的要求，并且计算负载也很高。在我们的研究中，我们通过数值模拟和实验研究了矩阵阵列孔径大小、元件数量和波束形成方法对定义的图像指标的影响。利用数值Vokurka模型，模拟了矩阵阵列对空化信号的采集。在实验部分，使用了两个具有不同间距和孔径大小的32×32矩阵阵列。在重建为三维空化图后，计算定义的指标以对实验数据和数值数据进行定量比较。数值结果表明，孔径从5毫米扩大到40毫米，半高宽（FWHM）在横向和轴向尺寸上分别提高了6倍和13倍。更大的阵列稀疏度对点扩散函数（PSF）的影响很小，而旁瓣电平（GLL）仍比主瓣低12分贝以上。这些结果在实验中得到了成功证实。为了进一步降低由阵列稀疏度引起的GLL，我们采用了一种来自光声的非线性滤波器用于PAM。结合延迟、乘法、求和与积分（DMSAI）算法，对于64元件重建，GLL降低了20分贝，达到了与全填充矩阵重建水平相同的水平。
