γ相机的实时数据采集与最大似然估计

Real-time Data Acquisition and Maximum-Likelihood Estimation for Gamma Cameras.

作者信息

Furenlid L R, Hesterman J Y, Barrett H H

机构信息

Department of Radiology and the College of Optical Sciences, University of Arizona, Tucson, AZ 85724 USA.

College of Optical Sciences, University of Arizona, Tucson, AZ 85724 USA.

出版信息

IEEE NPSS Real Time Conf. 2005 Jun;2005:498-501. doi: 10.1109/RTC.2005.1547506.

DOI:10.1109/RTC.2005.1547506

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4824558/

Abstract

We have developed modular gamma-ray cameras for biomedical imaging that acquire data with a raw list-mode acquisition architecture. All observations associated with a gamma-ray event, such as photomultiplier (PMT) signals and time, are assembled into an event packet and added to an ordered list of event entries that comprise the acquired data. In this work we present the design of the data-acquisition system, and discuss algorithms for a specialized computing engine to reside in the data path between the front and back ends of each camera and carry out maximum-likelihood position and energy estimations in real time while data was being acquired..

摘要

我们已经开发出用于生物医学成像的模块化伽马射线相机，其采用原始列表模式采集架构来获取数据。与伽马射线事件相关的所有观测值，如光电倍增管（PMT）信号和时间，都被组装成一个事件包，并添加到构成采集数据的事件条目的有序列表中。在这项工作中，我们展示了数据采集系统的设计，并讨论了一种专门计算引擎的算法，该引擎位于每个相机前端和后端之间的数据路径中，在采集数据时实时进行最大似然位置和能量估计。

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