Field-programable-gate-array-based distributed coincidence processor for high count-rate online positron emission tomography coincidence data acquisition.
Field-programable-gate-array-based distributed coincidence processor for high count-rate online positron emission tomography coincidence data acquisition.
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DOI：
10.1088/1361-6560/abde85
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发表时间：
2021-02-16
影响因子：
3.5
通讯作者：
Shao Y
中科院分区：
文献类型：
--
作者：
Cheng X;Hu K;Yang D;Shao Y
对于正电子发射断层扫描（PET）在线数据采集，具有单线程数据处理的集中式符合处理器（CCP）已被用于为许多PET扫描仪选择符合事件。CCP具有高度集成的电路、检测器前端和系统电子设备之间的紧凑连接以及数据处理和决策的集中控制的优点。但是，它也有数据处理延迟，难以处理非常高的计数率的单一和符合事件和复杂的算法来实现的缺点。当在现场可编程门阵列（FPGA）上实现CCP时，由于增加的路由拥塞和减少的数据吞吐量，这些问题加剧。行业公司已经应用非集中式或分布式数据处理来解决这些问题，但这些解决方案仍然是专有的，或者缺乏技术细节的充分披露，使得这些技术不清楚，难以适应大多数研究社区。在这项研究中，我们研究了使用一组分布式符合处理器（DCP），可以解决CCP的问题，并实现相对容易。每个符合处理器专门连接一个探测器对，并只从该探测器对中选择符合事件，这将集中的符合过程分解为独立和并行过程的集合。DCP可以显著地最小化数据处理延迟，最大化符合事件的计数率，并且通过用一个探测器对实现单个符合处理器并将其复制到其余探测器对来简化实现。在现成的FPGA开发板上实现了具有42个符合处理器的原型DCP，用于小型PET，该小型PET具有12个探测器，配置有42个探测器对。DCP的性能进行了测试与脉冲信号和伽马射线的相互作用。在探测器的最大单粒子计数率（250 k s-1）下，没有重合数据丢失。每个符合处理器使用大约1.2k个寄存器，FPGA资源利用率与符合处理器的数量成正比。符合时序谱显示了准确获取符合事件的结果。最后：作为CCP的补充，DCP可以提供高计数率能力，具有用于实现的简化算法，并且可能是用于使用大量探测器对的PET的在线采集或用于超高通量成像的实用解决方案。
For positron emission tomography (PET) online data acquisition, a centralized coincidence processor (CCP) with single-thread data processing has been used to select coincidence events for many PET scanners. A CCP has the advantages of highly integrated circuit, compact connection between detector front-end and system electronics and centralized control of data process and decision making. However, it also has the drawbacks of data process delay, difficulty in handling very high count-rates of single and coincidence events and complicated algorithms to implement. These problems are exacerbated when implementing a CCP on a field-programable-gate-array (FPGA) due to increased routing congestion and reduced data throughput. Industry companies have applied non-centralized or distributed data processing to solve these problems, but those solutions remain either proprietary or lack full disclosure of technical details that make the techniques unclear and difficult to adapt for most research communities. In this study, we investigated the use of a set of distributed coincidence processors (DCP) that can address the CCP problems and be implemented relatively easily. Each coincidence processor exclusively connects one detector pair and selects coincidence events from this detector pair only, which breaks a centralized coincidence process to a collection of independent and parallel processes. DCP can significantly minimize the data process delay, maximize count-rates of coincidence events and simplify implementation by implementing a single coincidence processor with one detector pair and replicating it to the rest. A prototype DCP with 42 coincidence processors was implemented on an off-the-shelf FPGA development board for a small PET with 12 detectors configured with 42 detector pairs. DCP performances were tested with both pulsed signals and gamma ray interactions. There was no coincidence data loss up to the detector’s maximum singles count-rate (250 k s−1). Approximately 1.2 k registers were utilized for each coincidence processor and the FPGA resource utilization was proportional to the number of coincidence processors. Coincidence timing spectra showed the results from accurately acquired coincidence events. In conclusion: complementary to CCP, DCP can provide high count-rate capability, with a simplified algorithm for implementation and potentially a practical solution for online acquisition of a PET with a larger number of detector pairs or for ultrahigh-throughput imaging.