论文标题
SPECT的基于列表模式OSEM的衰减和分散补偿方法
A list-mode OSEM-based attenuation and scatter compensation method for SPECT
论文作者
论文摘要
可靠的衰减和分散补偿（ASC）是定量的先决条件，对SPECT中的视觉解释任务有益。在本文中，我们开发了一种重建方法，该方法使用整个光谱发射数据，即Photopeak和Scacter Windows中的数据，以列表模式格式获得，包括检测到的光子的能量属性来执行ASC。我们使用有序子集期望最大化（OSEM）算法实现了基于GPU的该方法。使用现实的模拟研究对该方法进行了客观评估，该研究在二-D多巴胺转运蛋白（DAT）-SCAN SPECT研究中估计大脑纹状体区域摄取的任务。我们观察到，与仅使用Photopopeak窗口或使用BINNED DATA的数据相比，从散点窗口中包含数据并使用列表模式数据得到了改进的定量。这些结果激发了基于列表模式的ASC方法的进一步开发，其中包括SPECT的散点窗口数据。
Reliable attenuation and scatter compensation (ASC) is a prerequisite for quantification and beneficial for visual interpretation tasks in SPECT. In this paper, we develop a reconstruction method that uses the entire SPECT emission data, i.e. data in both the photopeak and scatter windows, acquired in list-mode format and including the energy attribute of the detected photon, to perform ASC. We implemented a GPU-based version of this method using an ordered subsets expectation maximization (OSEM) algorithm. The method was objectively evaluated using realistic simulation studies on the task of estimating uptake in the striatal regions of the brain in a 2-D dopamine transporter (DaT)-scan SPECT study. We observed that inclusion of data from the scatter window and using list-mode data yielded improved quantification compared to using data only from the photopeak window or using binned data. These results motivate further development of list-mode-based ASC methods that include scatter-window data for SPECT.
