首页> 外文OA文献 >Vollständige iterative Rekonstruktion von dreidimensionalen Positronen-Emissions-Tomogrammen unter Einsatz einer speicherresidenten Systemmatrix auf Single- und Multiprozessor-Systemen
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Vollständige iterative Rekonstruktion von dreidimensionalen Positronen-Emissions-Tomogrammen unter Einsatz einer speicherresidenten Systemmatrix auf Single- und Multiprozessor-Systemen

机译:在单处理器和多处理器系统上使用驻留于内存的系统矩阵完成三维正电子发射断层图的完全迭代重建

摘要

Positron emission tomography (PET) is a modern medical diagnostic procedure, which enables non invasive views of the metabolism of living organisms. Thereby it visualises also malfunctions which are characteristic for neurological, cardiological and oncological illnesses. For this purpose, radioactive, positron emitting tracers are injected into the patient. The emitted radiation is measured by detector systems and images of the activity distribution are calculated by reconstruction procedures. Newer, high sensitive PET devices with 3D detector systems pose substantial, so far yet unaccomplishable demands to the reconstruction programs because of the complexity and size of data. In this work a procedure is presented, with which the reconstruction problem is represented as linear equation system (LES). Methods are developed and implemented, in order to calculate the coefficient matrix of the LES exactly as well as efficiently and to compress it so extensively, that it can be stored completely in memory. Here the LES can be solved by means of a fast converging, iterative approximation method in short computation time. In addition, the well-established Ordered-Subset-MLEM algorithm is parallelized, the subset partitioning is improved, and the handling sequence of the subsets is optimized. This method of reconstruction is superior to known procedures regarding image quality and computation time.
机译:正电子发射断层扫描(PET)是一种现代医学诊断程序,可对生物体的新陈代谢进行非侵入式观察。因此,它还可视化了神经系统疾病,心脏病和肿瘤疾病所特有的故障。为此,将放射性正电子发射示踪剂注入患者体内。通过探测器系统测量发射的辐射,并通过重建程序计算活动分布的图像。带有3D检测器系统的新型高灵敏PET设备由于数据的复杂性和大小而对重建程序提出了巨大但迄今为止无法实现的要求。在这项工作中,提出了一个程序,用该程序将重建问题表示为线性方程组(LES)。为了精确有效地计算LES的系数矩阵并将其压缩得如此之大,以致可以将其完全存储在内存中,开发并实施了各种方法。在这里,LES可以通过快速收敛的迭代近似方法在较短的计算时间内解决。此外,完善了已有的有序子集-MLEM算法,改进了子集划分,并优化了子集的处理顺序。这种重建方法优于有关图像质量和计算时间的已知过程。

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  • 作者

    Kehren Frank;

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  • 年度 2001
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  • 原文格式 PDF
  • 正文语种 ger
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