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A Novel Method of Correcting the Sinogram Data for Postrion Emission Tomography

机译:校正射线发射层析成像的Singram数据的新方法

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In the problems of statistical reconstruction of PET images, Bayesian reconstruction, or maximum a posteriori (MAP) method, has proved its superiority over others among all the regularization methods. To further improve the reconstruction, this paper presents a novel statistical image reconstruction method based on coupled feedback (CF) iterative model for positron emission tompgraphy (PET). This CF iterative algorithm updates the noisy emission sinogram (the measurements of the detectors) using the latest reconstructed image. The experiments and the performance analysis confirm the virtue of the new method.
机译:在PET图像的统计重建问题中,贝叶斯重建或最大后验(MAP)方法已证明其在所有正则化方法中均优于其他方法。为了进一步改善重建效果,本文提出了一种基于耦合反馈(CF)迭代模型的正电子发射断层扫描(PET)统计图像重建方法。该CF迭代算法使用最新的重建图像更新噪声发射正弦图(检测器的测量值)。实验和性能分析证实了该新方法的优越性。

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