Interdisciplinary Program of Bioengineering, Seoul National University, Seoul, Republic of Korea.
Integrated Major in Innovative Medical Science, Seoul National University Graduate School, Republic of Korea.
Phys Med Biol. 2023 May 22;68(11). doi: 10.1088/1361-6560/acd163.
Identifying the inter-crystal scatter (ICS) events and recovering the first interaction position enables the accurate determination of the line-of-response in positron emission tomography (PET). However, conventional silicon photomultiplier (SiPM) signal multiplexing methods based on two-dimensional (2D) charge-division circuits do not allow the detection of multiple gamma-ray interaction positions in a scintillation array coupled with a SiPM array. In this study, we propose a novel multiplexing method that can restore all the individual channel data from a smaller number of multiplexed channels using high-pass filters and neural networks.The number of output channels is reduced by summing the SiPM signals that have passed through high-pass filters with different time constants. Then, the signal amplitude of each SiPM channel is restored from the combined signal using an artificial neural network. This study explains the principle of this method in detail and demonstrates the results using 4:1 multiplexing as an example. The usefulness of this method was also demonstrated by its application in the identification of ICS events in 1-to-1 coupled LSO-SiPM PET detectors.The artificial neural network enabled accurate energy estimation for each SiPM channel. One of the high-pass filter sets with the lowest Cramér-Rao lower bound provided the best results, yieldingvalue of 0.99 between the true and estimated signals. The energy and flood histograms generated using the best-estimated signals were in good agreement with the ground truth. Additionally, the proposed method accurately estimated 2D energy deposit distribution in the LSO crystal array, allowing ICS event identification.The proposed method is potentially useful for ICS event recovery with a reduced number of array signal readout channels from a SiPM array.
识别晶间散射(ICS)事件并恢复首次相互作用位置,可实现正电子发射断层扫描(PET)中响应线的精确确定。然而,基于二维(2D)电荷分割电路的传统硅光电倍增管(SiPM)信号复用方法,无法在与 SiPM 阵列耦合的闪烁体阵列中检测多个伽马射线相互作用位置。在这项研究中,我们提出了一种新颖的复用方法,该方法可以使用高通滤波器和神经网络从较少的复用通道中恢复所有单个通道数据。通过对具有不同时间常数的高通滤波器的 SiPM 信号进行求和,减少输出通道的数量。然后,使用人工神经网络从组合信号中恢复每个 SiPM 通道的信号幅度。本研究详细解释了该方法的原理,并以 4:1 复用为例展示了结果。通过将该方法应用于 1-1 耦合 LSO-SiPM PET 探测器中的 ICS 事件识别,也证明了该方法的有效性。人工神经网络能够为每个 SiPM 通道进行准确的能量估计。一组具有最低克拉美罗下界的高通滤波器提供了最佳结果,真实信号和估计信号之间的值为 0.99。使用最佳估计信号生成的能量和洪水直方图与真实值非常吻合。此外,该方法还可以准确估计 LSO 晶体阵列中的 2D 能量沉积分布,从而实现 ICS 事件识别。该方法有望通过减少 SiPM 阵列中阵列信号读出通道的数量来实现 ICS 事件恢复。