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Software-Based Real-Time Acquisition and Processing of PET Detector Raw Data

机译:基于软件的PET检测器原始数据的实时采集和处理

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In modern positron emission tomography (PET) readout architectures, the position and energy estimation of scintillation events (singles) and the detection of coincident events (coincidences) are typically carried out on highly integrated, programmable printed circuit boards. The implementation of advanced singles and coincidence processing (SCP) algorithms for these architectures is often limited by the strict constraints of hardware-based data processing. In this paper, we present a software-based data acquisition and processing architecture (DAPA) that offers a high degree of flexibility for advanced SCP algorithms through relaxed real-time constraints and an easily extendible data processing framework. The DAPA is designed to acquire detector raw data from independent (but synchronized) detector modules and process the data for singles and coincidences in real-time using a center-of-gravity (COG)-based, a least-squares (LS)-based, or a maximum-likelihood (ML)-based crystal position and energy estimation approach (CPEEA). To test the DAPA, we adapted it to a preclinical PET detector that outputs detector raw data from 60 independent digital silicon photomultiplier (dSiPM)-based detector stacks and evaluated it with a [F]-fluorodeoxyglucose-filled hot-rod phantom. The DAPA is highly reliable with less than 0.1% of all detector raw data lost or corrupted. For high validation thresholds (37.1  12.8 photons per pixel) of the dSiPM detector tiles, the DAPA is real time capable up to 55 MBq for the COG-based CPEEA, up to 31 MBq for the LS-based CPEEA, and up to 28 MBq for the ML-based CPEEA. Compared to the COG-based CPEEA, the rods in the image reconstruction of the hot-rod phantom are only slightly better separable and less blurred for the LS- and ML-based CPEEA. While the coincidence time resolution - 550 ps) and energy resolution (12.3%) are comparable for all three CPEEA, the system sensitivity is up to 2.5 higher for the LS- and ML-based CPEEA.
机译:在现代的正电子发射断层扫描(PET)读出体系结构中,闪烁事件(单个)的位置和能量估计以及重合事件(重合)的检测通常在高度集成的可编程印刷电路板上进行。对于这些体系结构,高级单打和符合处理(SCP)算法的实现通常受到基于硬件的数据处理的严格限制。在本文中,我们提出了一种基于软件的数据采集和处理架构(DAPA),该架构通过宽松的实时约束和易于扩展的数据处理框架为高级SCP算法提供了高度的灵活性。 DAPA旨在从独立(但已同步)的检测器模块中获取检测器原始数据,并使用基于重心(COG)的最小二乘(LS)实时处理单点和巧合数据。或基于最大似然(ML)的晶体位置和能量估计方法(CPEEA)。为了测试DAPA,我们将其适配于临床前PET检测器,该检测器从基于60个独立数字硅光电倍增管(dSiPM)的检测器堆栈中输出检测器原始数据,并使用填充了[F]-氟脱氧葡萄糖的热棒体模对其进行了评估。 DAPA高度可靠,丢失或损坏的所有探测器原始数据不到0.1%。对于dSiPM检测器磁贴的高验证阈值(每像素37.1 12.8光子),DAPA实时支持基于COG的CPEEA高达55 MBq,基于LS的CPEEA高达31 MBq和高达28 MBq基于ML的CPEEA。与基于COG的CPEEA相比,对于基于LS和ML的CPEEA,热棒体模图像重建中的棒仅具有更好的可分离性,并且模糊程度更低。虽然这三种CPEEA的重合时间分辨率-550 ps)和能量分辨率(12.3%)都是可比的,但基于LS和ML的CPEEA的系统灵敏度高达2.5。

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