Achievable resolution for scalable Waveform Digitizing PET readout and comparison with ideal TDC-based readout with an application of DNN to optimal estimation including DOI.

L Macchiarulo, C Chock, I Mostafanezhad, H Sabet
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Abstract

Time Of Flight PET (TOF-PET) is a transformative technology for PET systems, but reaping its fullest potential requires achieving very high spatial and timing resolution, and overcoming dependency on signal variability at the level of the individual pixels. In this study, we try to quantify the advantage of using custom waveform sampling devices versus TDC methodology using realistic estimates of noise and other non-idealities. With the use of DNN methodology we show achievable gain for current and future acquisition systems, and also demonstrate the feasibility of DOI estimation from single side readout. We conclude by arguing for the scalability of such a system based on our experience with compact waveform digitizer design.

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数字化PET读数,并与理想的基于tdc的读数进行比较,并应用深度神经网络进行最优估计,包括DOI。
飞行时间PET (TOF-PET)是PET系统的一项变革性技术,但要充分发挥其潜力,需要实现非常高的空间和时间分辨率,并克服对单个像素级信号可变性的依赖。在本研究中,我们试图通过对噪声和其他非理想情况的实际估计来量化使用自定义波形采样设备与TDC方法的优势。通过使用深度神经网络方法,我们展示了当前和未来采集系统可实现的增益,并且还展示了从单侧读出估计DOI的可行性。最后,我们根据我们在紧凑型波形数字化仪设计方面的经验,论证了这种系统的可扩展性。
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