实现散射校正列表模式的OP-EM重建算法和动态PET成像的双重(直方图/列表模式)重建方案

J. Cheng, A. Rahmim, S. Blinder, M. Camborde, V. Sossi
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引用次数: 9

摘要

利用基于单散射模拟(SSS)技术的散点校正方法和基于方差减少延迟重合技术的随机校正方法实现了高分辨率研究层析成像(HRRT)的普通泊松列表模式期望最大化(OP-LMEM)算法。在列表模式重建(H-LMEM)中也实现了一种混合EM算法,该算法使用延迟符合事件减法技术,散点校正与OP-LMEM相同。将对比幻影动态扫描序列的重建图像与直方图模式重建图像进行了比较,特别是具有相同方差减少随机和估计散点的三维普通泊松有序子集期望最大化(3D- op)重建图像。跨轴和轴向剖面分析显示直方图和两种列表模式重建之间具有良好的一致性。同样,初步的对比和噪声分析表明直方图模式和列表模式重建之间的密切一致。基于这些结果,双重重建方案现在可以应用于散射校正的正电子发射断层扫描(PET)的动态成像;即直方图模式重建(3D-OP)可以应用于具有大量计数的帧,列表模式重建(OP-LMEM)随后将用于低统计帧,以获得适用于使用HRRT的最先进的动态PET成像的高效和定量准确的重建。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of scatter corrected list-mode OP-EM reconstruction algorithm and a dual (histogram/list-mode) reconstruction scheme for dynamic PET imaging
We describe an implementation of ordinary Poisson list-mode expectation maximization (OP-LMEM) algorithm for the high resolution research tomography (HRRT) with a scatter correction method based on the single scatter simulation (SSS) technique, and a random correction method based on the variance-reduced delayed-coincidence technique. A hybrid EM algorithm has also been implemented in list-mode reconstruction (H-LMEM) using delayed-coincidence event subtraction technique with the same scatter correction as in OP-LMEM. The reconstructed images of a dynamic scanning sequence of a contrast phantom have been compared with those reconstructed using the histogram-mode reconstruction, in particular, 3D ordinary Poisson ordered subset expectation maximization (3D-OP) with the same variance-reduced random and estimated scatter. The transaxial and axial profile analyses have shown excellent agreement between histogram and both list-mode reconstructions. Likewise the preliminary contrast and noise analyses have shown a close agreement between histogram-mode and both list-mode reconstructions. Based on these results, a dual reconstruction scheme can now be applied to dynamic imaging in positron emission tomography (PET) with scatter correction; i.e. histogram-mode reconstruction (3D-OP) can be applied to frames with a large number of counts, and list-mode reconstruction (OP-LMEM) will subsequently be used for low statistics frames, as an effort to obtain efficient and quantitatively accurate reconstructions applicable to state-of-the-art dynamic PET imaging using the HRRT.
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