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首页> 外文期刊>Physics in medicine and biology. >A new virtual ring-based system matrix generator for iterative image reconstruction in high resolution small volume PET systems
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A new virtual ring-based system matrix generator for iterative image reconstruction in high resolution small volume PET systems

机译:基于虚拟环的系统矩阵发生器,用于高分辨率小卷PET系统中的迭代图像重建

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A common approach to improving the spatial resolution of small animal PET scanners is to reduce the size of scintillation crystals and/or employ high resolution pixellated semiconductor detectors. The large number of detector elements results in the system matrix-an essential part of statistical iterative reconstruction algorithms-becoming impractically large. In this paper, we propose a methodology for system matrix modelling which utilises a virtual single-layer detector ring to greatly reduce the size of the system matrix without sacrificing precision. Two methods for populating the system matrix are compared; the first utilises a geometrically-derived system matrix based on Siddon's ray tracer method with the addition of an accurate detector response function, while the second uses Monte Carlo simulation to populate the system matrix. The effectiveness of both variations of the proposed technique is demonstrated via simulations of PETiPIX, an ultra high spatial resolution small animal PET scanner featuring high-resolution DoI capabilities, which has previously been simulated and characterised using classical image reconstruction methods. Compression factors of 5 x 10(7) and 2.5 x 10(7) are achieved using this methodology for the system matrices produced using the geometric and Monte Carlo-based approaches, respectively, requiring a total of 0.5-1.2 GB of memory-resident storage. Images reconstructed from Monte Carlo simulations of various point source and phantom models, produced using system matrices generated via both geometric and simulation methods, are used to evaluate the quality of the resulting system matrix in terms of achievable spatial resolution and the CRC, CoV and CW-SSIM index image quality metrics. The Monte Carlo-based system matrix is shown to provide the best image quality at the cost of substantial one-off computational effort and a lower (but still practical) compression factor. Finally, a straightforward extension of the virtual ring method to a three dimensional virtual cylinder is demonstrated using a 3D DoI PET scanner.
机译:一种常见的改进小动物PET扫描仪的空间分辨率的方法是减小闪烁晶体的尺寸和/或采用高分辨率的像素半导体检测器。大量检测器元件导致系统矩阵 - 统计迭代重建算法的重要组成部分 - 变得不切实际。在本文中,我们提出了一种用于系统矩阵建模的方法,其利用虚拟单层检测器环大大减小系统矩阵的大小而不牺牲精度。比较了填充系统矩阵的两种方法;首先利用基于Siddon的射线示踪方法的几何衍生系统矩阵,添加了准确的检测器响应函数,而第二种使用Monte Carlo仿真填充系统矩阵。通过Petipix的模拟证明了所提出的技术的两种变化的有效性,超高空间分辨率小动物PET扫描仪,其先前已经使用经典图像重建方法进行了模拟和表征。使用该方法的压缩因子,使用该方法,用于使用基于几何和蒙特卡罗的方法产生的系统矩阵,总共需要0.5-1.2 GB的内存居民贮存。从各种点源和幻像模型重建的图像,使用通过几何和仿真方法产生的系统矩阵产生的,用于评估可实现的空间分辨率和CRC,COV和CW所产生的系统矩阵的质量-sim索引图像质量指标。基于Monte Carlo的系统矩阵被示出为提供最佳的图像质量,以实质的一次性计算工作和较低(但仍然实用)压缩因子的成本提供最佳的图像质量。最后,使用3D DOI PET扫描仪演示虚拟环方法到三维虚拟圆柱体的直接扩展。

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