Improving Depth, Energy and Timing Estimation in PET Detectors with Deconvolution and Maximum Likelihood Pulse Shape Discrimination.
Improving Depth, Energy and Timing Estimation in PET Detectors with Deconvolution and Maximum Likelihood Pulse Shape Discrimination.
复制标题
DOI：
10.1109/tmi.2016.2577539
复制
发表时间：
2016-11
影响因子：
10.6
通讯作者：
Cherry SR
中科院分区：
文献类型：
--
作者：
Berg E;Roncali E;Hutchcroft W;Qi J;Cherry SR
在闪烁探测器中，通过伽马相互作用在闪烁体中产生的光被光电探测器转换为光电子，并产生时间相关波形，其形状取决于闪烁体特性和光电探测器响应。已经开发了几种相互作用深度（DOI）编码策略，其沿着晶体长度沿着操纵闪烁体的时间响应，因此需要脉冲形状鉴别技术来区分波形形状。在这项工作中，我们演示了如何最大似然（ML）估计方法可以应用到脉冲形状歧视，以更好地估计沉积的能量，DOI和相互作用时间（飞行时间（TOF）PET）的γ射线在闪烁探测器。我们开发的可能性模型的基础上估计的检测时间的单个光电子或离散时间仓中的光电子的数量，并适用于两个荧光粉涂层的晶体（LFS和LYSO）在以前开发的TOF-DOI检测器的概念。与传统的分析方法相比，ML脉冲形状歧视提高了27%的DOI编码的晶体。使用ML DOI估计，我们能够对抗长闪烁体晶体固有的光收集的深度依赖性变化，并恢复用固定深度照射测量的能量分辨率（两种晶体约为11.5%）。最后，我们演示了如何将Richardson-Lucy算法（一种基于ML的迭代反卷积技术）应用于数字化波形，以反卷积光电探测器的单个光电子响应并产生具有更快上升沿的波形。在去卷积和应用DOI和时间行走校正后，我们证明了LFS晶体的符合时间分辨率（从290到254 ps）提高了13%，LYSO晶体提高了8%（323到297 ps）。
In a scintillation detector, the light generated in the scintillator by a gamma interaction is converted to photoelectrons by a photodetector and produces a time-dependent waveform, the shape of which depends on the scintillator properties and the photodetector response. Several depth-of-interaction (DOI) encoding strategies have been developed that manipulate the scintillator’s temporal response along the crystal length and therefore require pulse shape discrimination techniques to differentiate waveform shapes. In this work, we demonstrate how maximum likelihood (ML) estimation methods can be applied to pulse shape discrimination to better estimate deposited energy, DOI and interaction time (for time-of-flight (TOF) PET) of a gamma ray in a scintillation detector. We developed likelihood models based on either the estimated detection times of individual photoelectrons or the number of photoelectrons in discrete time bins, and applied to two phosphor-coated crystals (LFS and LYSO) used in a previously developed TOF-DOI detector concept. Compared with conventional analytical methods, ML pulse shape discrimination improved DOI encoding by 27% for both crystals. Using the ML DOI estimate, we were able to counter depth-dependent changes in light collection inherent to long scintillator crystals and recover the energy resolution measured with fixed depth irradiation (~11.5% for both crystals). Lastly, we demonstrated how the Richardson-Lucy algorithm, an iterative, ML-based deconvolution technique, can be applied to the digitized waveforms to deconvolve the photodetector’s single photoelectron response and produce waveforms with a faster rising edge. After deconvolution and applying DOI and time-walk corrections, we demonstrated a 13% improvement in coincidence timing resolution (from 290 to 254 ps) with the LFS crystal and an 8% improvement (323 to 297 ps) with the LYSO crystal.