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High-Resolution Image Reconstruction for PET using Estimated Detector Response Functions

机译:利用估计的检测器响应函数重建PET的高分辨率图像

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摘要

The accuracy of the system model in an iterative reconstruction algorithm greatly affects the quality of reconstructed PET images. For efficient computation in reconstruction, the system model in PET can be factored into a product of geometric projection matrix and detector blurring matrix, where the former is often computed based on analytical calculation, and the latter is estimated using Monte Carlo simulations. In this work, we propose a method to estimate the 2D detector blurring matrix from experimental measurements. Point source data were acquired with high-count statistics in the microPET II scanner using a computer-controlled 2-D motion stage. A monotonically convergent iterative algorithm has been derived to estimate the detector blurring matrix from the point source measurements. The algorithm takes advantage of the rotational symmetry of the PET scanner with the modeling of the detector block structure. Since the resulting blurring matrix stems from actual measurements, it can take into account the physical effects in the photon detection process that are difficult or impossible to model in a Monte Carlo simulation. Reconstructed images of a line source phantom show improved resolution with the new detector blurring matrix compared to the original one from the Monte Carlo simulation. This method can be applied to other small-animal and clinical scanners.
机译:迭代重建算法中系统模型的准确性极大地影响了重建PET图像的质量。为了高效地进行重建计算,可以将PET中的系统模型分解为几何投影矩阵和检测器模糊矩阵的乘积,其中前者通常是基于解析计算来计算的,而后者则是使用蒙特卡洛模拟来估算的。在这项工作中,我们提出了一种从实验测量值估计二维检测器模糊矩阵的方法。使用计算机控制的二维运动平台,在microPET II扫描仪中以高计数统计数据获取点源数据。已经得出了单调收敛的迭代算法,以根据点源测量值来估计检测器模糊矩阵。该算法利用了PET扫描仪的旋转对称性以及检测器块结构的建模功能。由于生成的模糊矩阵源自实际测量,因此可以考虑在光子检测过程中很难或不可能在蒙特卡洛模拟中建模的物理效应。与新的检测器模糊矩阵相比,线源体模的重建图像显示出更高的分辨率,这与蒙特卡罗模拟中的原始图像相比。该方法可以应用于其他小型动物和临床扫描仪。

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