Caucci Luca, Hunter William C J, Furenlid Lars R, Barrett Harrison H
College of Optical Sciences, University of Arizona, Tucson, AZ 85721 and also with the Center for Gamma-Ray Imaging, University of Arizona, Tucson, AZ 85719.
IEEE Nucl Sci Symp Conf Rec (1997). 2010 Oct;2010:2643-2647. doi: 10.1109/NSSMIC.2010.5874269.
Current thick detectors used in medical imaging allow recording many attributes, such as the 3D location of interaction within the scintillation crystal and the amount of energy deposited. An efficient way of dealing with these data is by storing them in list-mode (LM). To reconstruct the data, maximum-likelihood expectation-maximization (MLEM) is efficiently applied to the list-mode data, resulting in the list-mode maximum-likelihood expectation-maximization (LMMLEM) reconstruction algorithm.In this work, we consider a PET system consisting of two thick detectors facing each other. PMT outputs are collected for each coincidence event and are used to perform 3D maximum-likelihood (ML) position estimation of location of interaction. The mathematical properties of the ML estimation allow accurate modeling of the detector blur and provide a theoretical framework for the subsequent estimation step, namely the LMMLEM reconstruction. Indeed, a rigorous statistical model for the detector output can be obtained from calibration data and used in the calculation of the conditional probability density functions for the interaction location estimates.Our implementation of the 3D ML position estimation takes advantage of graphics processing unit (GPU) hardware and permits accurate real-time estimates of position of interaction. The LMMLEM algorithm is then applied to the list of position estimates, and the 3D radiotracer distribution is reconstructed on a voxel grid.
当前医学成像中使用的厚探测器能够记录许多属性，例如闪烁晶体内相互作用的三维位置以及沉积的能量数量。处理这些数据的一种有效方法是将它们存储在列表模式（LM）中。为了重建数据，最大似然期望最大化（MLEM）被有效地应用于列表模式数据，从而产生了列表模式最大似然期望最大化（LMMLEM）重建算法。在这项工作中，我们考虑一个由两个相对的厚探测器组成的正电子发射断层扫描（PET）系统。对于每个符合事件，收集光电倍增管（PMT）输出，并用于对相互作用位置进行三维最大似然（ML）位置估计。ML估计的数学特性允许对探测器模糊进行精确建模，并为后续的估计步骤，即LMMLEM重建提供理论框架。实际上，可以从校准数据中获得探测器输出的严格统计模型，并用于计算相互作用位置估计的条件概率密度函数。我们对三维ML位置估计的实现利用了图形处理单元（GPU）硬件，并允许对相互作用位置进行精确的实时估计。然后将LMMLEM算法应用于位置估计列表，并在体素网格上重建三维放射性示踪剂分布。
