Gholampour Amir, Cano Camilo, van Sambeek Marc R H M, Lopata Richard, Wu Min, Schwab Hans-Martin
Photoacoustics and Ultrasound Laboratory Eindhoven (PULS/e), Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, 5600 MB, The Netherlands.
Department of Vascular Surgery, Catharina Hospital Eindhoven, Eindhoven, 5602 ZA, The Netherlands.
Photoacoustics. 2024 Feb 23;37:100598. doi: 10.1016/j.pacs.2024.100598. eCollection 2024 Jun.
Photoacoustic imaging creates light-induced ultrasonic signals to provide valuable information on internal body structures and tissue morphology non-invasively. A multi-aperture photoacoustic imaging (MP-PAI) system is an improvement over conventional photoacoustic imaging (PAI) systems in terms of resolution, contrast, and field of view. Previously, a prototype MP-PAI system was introduced based on multiple capacitive micromachined ultrasound transducers (CMUTs) with shared channels, such that each element in a CMUT shares its channel with its counterpart in other CMUTs. The system uses the biasing voltages of the CMUTs to switch between them and multiplex the received signals in time. Notwithstanding all the enhancements, the signal-to-noise ratio (SNR) remains limited in PAI. To address this issue, we are proposing a multi-aperture encoding scheme (MAES) to further increase the SNR in a multi-aperture PAI system. The proposed method involves receiving signals with multiple CMUTs simultaneously based on an encoding matrix, instead of switching between individual CMUTs. As a result, shared channels contain a superposition of signals, which are later recovered by applying a decoding matrix. Here, an analytical model for computing SNR with an arbitrary encoding sequence is presented, and the method is validated through numerical simulations and in an experimental study. Bipolar and unipolar encoding sequences were considered for the experiments. The numerical results show, in comparison to conventional MP-PAI, that MAES will obtain an SNR gain of 5.8 and 8.8 dB for S-sequence and truncated Hadamard encodings, respectively, when using 15 transducers. In experiments, three transducers are encoded by S-sequences and show 1.5 dB improvement in SNR over conventional MP-PAI method, which aligns well with the analytical model.
光声成像利用光诱导产生超声信号，从而无创地提供关于人体内部结构和组织形态的有价值信息。多孔径光声成像（MP-PAI）系统在分辨率、对比度和视野方面相较于传统光声成像（PAI）系统有所改进。此前，基于具有共享通道的多个电容式微机械超声换能器（CMUT）引入了一个MP-PAI系统原型，使得CMUT中的每个元件与其在其他CMUT中的对应元件共享其通道。该系统利用CMUT的偏置电压在它们之间进行切换，并对接收信号进行时分复用。尽管有这些改进，但PAI中的信噪比（SNR）仍然有限。为了解决这个问题，我们提出了一种多孔径编码方案（MAES），以进一步提高多孔径PAI系统中的SNR。所提出的方法涉及基于编码矩阵同时用多个CMUT接收信号，而不是在各个CMUT之间进行切换。结果，共享通道包含信号的叠加，随后通过应用解码矩阵进行恢复。在此，给出了一个用于计算具有任意编码序列的SNR的解析模型，并通过数值模拟和实验研究对该方法进行了验证。实验考虑了双极性和单极性编码序列。数值结果表明，与传统MP-PAI相比，当使用15个换能器时，MAES对于S序列和截断哈达玛编码分别将获得5.8 dB和8.8 dB的SNR增益。在实验中，三个换能器采用S序列编码，与传统MP-PAI方法相比，SNR提高了1.5 dB，这与解析模型吻合得很好。
