Compressed sensing-based synthetic transmit aperture (CS-STA) was previously proposed to recover the full radio-frequency (RF) channel dataset of synthetic transmit aperture (STA) from that of a smaller number of randomly apodized plane wave (PW) transmissions. In this way, the imaging frame rate (FR) and contrast are improved with maintained spatial resolution, compared with those of STA. Because CS-STA reconstruction is repeated for all receive elements and RF samples (with a high sampling frequency), the recovery of STA dataset in RF domain is time-consuming. In the meantime, a large amount of RF data needs to be transferred and stored, resulting in an increase of system complexity and required memory space. In this study, CS-STA is extended to in-phase/quadrature (IQ) domain (with lower sampling frequency) for the recovery of baseband STA IQ dataset to accelerate the CS-STA reconstruction by reducing the amount of data to be processed. More importantly, CS-STA reconstruction using IQ data is of practical importance, as clinical ultrasound systems typically record baseband IQ signal instead of RF signal. Simulations, phantom and in vivo experiments verify the feasibility of CS-STA in IQ domain for the recovery of STA dataset. More specifically, CS-STA using IQ data achieves similar image quality and appreciably improves reconstruction speed (by ∼3 times) compared with that using RF data. These findings demonstrate that IQ-domain CS-STA is capable of relieving the computational and storage burdens, which may facilitate the implementation of CS-STA in practical ultrasound systems.

之前提出了基于压缩感知的合成发射孔径 (CS-STA)，以从较少数量的随机切趾平面波 (PW) 传输中恢复合成发射孔径 (STA) 的完整射频 (RF) 信道数据集。通过这种方式，与 STA 相比，在保持空间分辨率的情况下提高了成像帧率 (FR) 和对比度。由于对所有接收单元和 RF 样本（具有高采样频率）重复 CS-STA 重建，因此 RF 域中 STA 数据集的恢复非常耗时。同时，需要传输和存储大量射频数据，导致系统复杂度和所需存储空间增加。在这项研究中，CS-STA 扩展到同相/正交 (IQ) 域（具有较低采样频率）以恢复基带 STA IQ 数据集，通过减少要处理的数据量来加速 CS-STA 重建。更重要的是，使用 IQ 数据的 CS-STA 重建具有实际重要性，因为临床超声系统通常记录基带 IQ 信号而不是 RF 信号。模拟、幻影和体内实验验证了 IQ 域中 CS-STA 用于恢复 STA 数据集的可行性。更具体地说，与使用 RF 数据相比，使用 IQ 数据的 CS-STA 实现了相似的图像质量，并显着提高了重建速度（约 3 倍）。这些发现表明 IQ 域 CS-STA 能够减轻计算和存储负担，这可能有助于 CS-STA 在实际超声系统中的实施。