【作者】 都军伟；

【导师】 王永纲；

【作者基本信息】 中国科学技术大学 ， 物理电子学， 2010， 博士

【摘要】 正电子发射断层扫描成像(Positron Emission Tomography, PET)是一种核医学成像技术,它通过探测正电子核素衰变产生的γ射线成像,是一种无创伤,可以在分子水平上观察生物体组织新陈代谢的活体成像技术。近年,小动物PET和专用PET(如PEM, BrainPET)的研究越来越受到重视,引起许多研究者的兴趣。和人体用PET不同,这两类PET需要较高的分辨率以观察较小的生物体组织。当前,采用晶体阵列和多通道光电探测器相结合组成的PET探测器,普遍获得了小于2mm的位置分辨率。但是,在这类探测器中,晶体阵列间存在由隔光材料形成的死区,降低了探测器的灵敏度。同时,γ射线在晶体内部的散射和由反应深度造成的视差(Depth of Interaction,DOI)都可能恶化探测器的分辨率。作为一个选择,采用连续晶体组成的探测器可以避免这些问题。相对于晶体阵列型探测器,这种探测器的设计简单,造价低,灵敏区域大并且能量分辨率和时间分辨率都要好。在这种探测器中,晶体的选择可以大于光电转换器的灵敏区,覆盖包含光电转换器封装在内的面积。γ射线在晶体表面的入射位置,而非在晶体内部的作用位置可以通过γ射线和晶体作用后产生的光分布信息获得。在本文,我们采用LYSO晶体和多通道光电倍增管组成探测器实验模型,采用神经网络作为位置估算器。我们从测试探测器所需晶体的性能开始,对探测器实验模型的各个方面作了详细的介绍：包括优化64通道探测器信号读出方案,建立用于获取探测器信号的电子学系统及其相应上层控制软件,对电子学系统和探测器性能的测试,优化MLP网络参数的选者,在FPGA上实现了用于位置估算的网络算法。下面概要说明本文各章的主要内容。第一章是绪论,介绍了PET成像的基本原理及其性能指标,简要描述了PET两个应用。第二章介绍了PET探测器的组成以及几个典型的高分辨小动物PET系统所使用的探测器设计方法。第三章描述了神经网络的基本原理,主要介绍了多层感知器网络和径向基函数网络的结构以及学习方法。第四章是对我们所使用的LYSO晶体的性能测试,包括激发发射谱,荧光衰减时间,能量分辨率和光产额。第五章是对探测器的读出方案优化,描述了四种探测器信号读出方案对定位精度的影响。第六章详细介绍PET探测器实验平台的设计,包括电子学系统硬件和软件的设计,电子学系统的性能测试,探测器平台的组成和性能的初步测试。第七章详细描述由多通道光电倍增管H7546B和大块连续晶体LYSO组成的探测器性能,包括探测器的时间分辨率,能量分辨率和位置分辨率。第八章介绍了一个在FPGA中实现的,资源和速度有效折中的位置在线实时计算方案。第九章对本文的工作做了一个简要总结,并对目前和将来可进行的工作做了一个简要讨论。更多还原

【Abstract】 Positron emission tomography is a nuclear imaging technique that based on the detection of gamma rays. It is a noninvasive technologies allowing tracing in vivo metabolic function of the organism at molecular level.In recent years, the interest in small animal positron emission tomography (PET) and dedicated PET (like PEM and Brain PET) has increased dramatically, stimulating the development of detectors with high spatial resolution. The small dimensions of these animals and the organs of human impose stringent requirements on the high spatial resolution and sensitivity of those PET systems. Current designs based on matrices of individual crystal pixels have achieved an intrinsic spatial resolution better than 2mm. But the detection efficiency in these pixelated detector designs is reduced due to the dead space introduced by the reflective material between the crystals. Additionally, the spatial resolution may be deteriorated by inter-crystal scatter and parallax errors because of depth of interaction (DOI) effects.Alternatively, detector based on large continuous scintillator blocks results in a higher sensitivity since there is no dead space due to material needed to optically separate individual pixels. Those detectors have the advantage of simple design, lower cost, better energy and time resolution, compared with the pixilated ones. The size of monolithic crystals can even be chosen such that they completely cover the photo detectors used to read out the scintillation light, including the packaging. The entry point of a detected 511 keV photon on the surface of the crystal, instead of the interaction position is determined from the distribution of the scintillation light using a non-anger position algorithm, such as neural network, nearest neighbor and statistics based positioning algorithm, etc.We are currently developing a practical implementation of prototype monolithic scintillator PET detector modules with neural network position algorithm. This thesis gives a detailed description of this PET detector prototype, including the measurement of the physical properties of the LYSO scintillator, the optimization of signal readout scheme from the MC-PMT, the design and test of the electronics system and the experimental PET prototype, the FPGA implement of neural network position estimator, etc.The following outlines the contents of each chapter in this thesis briefly. The first chapter is the preface, situates PET in the molecular imaging world and introduces the principle of PET imaging, imaging and scanner performance, two examples of application.The second chapter introduces the components of PET detector and the design scheme of several high resolution small animal PET systems.The third chapter depicts the basic principle of neural network and mainly introduces the structure and learning methods of MLP (Multiplier perceptron) and RBF (Radial Basis Function) networks when they are used to solve a regression problem (function approximation).The fourth chapter demonstrates the physical properties of the LYSO scintillator measured by ourselves, including emission spectra, decay time, energy resolution and light output.The fifth chapter illustrates the optimization and its affect on spatial resolution of four possible signal readout geometries through combinations of the 64 channels signal from PMT before the digitization by Monte Carlo simulation using Geant4.The sixth chapter gives a detail of the design of the experiments PET detector prototype, including the design and test of the hardware and software of the electrical system, the components and the primary measurements of the detector prototype.The seventh chapter presents an overview of the performance of monolithic scintillator detectors based on LYSO crystal and MC-PMT H7546B and several methods to chose the hidden neurons number of MLP NN. The investigation includes timing resolution, energy resolution and spatial resolution.The eighth chapter describes a performance and resource efficient architecture to realize on-line neural network position estimating for PET detector modules. The implementation of network is based on FPGA.The ninth chapter is the conclusion of this thesis. The innovation and future work are presented.更多还原