Restoration of lost frequency in OpenPET imaging: comparison between the method of convex projections and the maximum likelihood expectation maximization method
Restoration of lost frequency in OpenPET imaging: comparison between the method of convex projections and the maximum likelihood expectation maximization method
复制标题
OpenPET 成像中丢失频率的恢复：凸投影方法与最大似然期望最大化方法的比较
DOI：
10.1007/s12194-014-0270-5
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发表时间：
2014
影响因子：
1.6
通讯作者：
Taiga Yamaya
中科院分区：
文献类型：
--
作者：
Hideaki Tashima;Takayuki Katsunuma;Hiroyuki Kudo;Hideo Murayama;Takashi Obi;Mikio Suga;Taiga Yamaya
我们正在开发一种基于“OpenPET”几何结构的新型PET扫描仪，它由两个由间隙隔开的探测器环组成。必须注意的一点是，OpenPET图像重建被归类为一个不完全逆问题，其中低频分量被截断。然而，在我们以前的模拟和实验中，通过应用迭代图像重建方法使得OpenPET成像是可行的。因此，我们期望迭代方法具有恢复作用，以补偿丢失的频率。在存在数据截断的情况下，改善图像质量的重建方法有两种：一种是迭代方法，如最大似然期望最大化(ML-EM)；另一种是解析图像重建方法，然后是凸投影法，这在OpenPET中还没有被采用。因此，在本研究中，我们提出了一种将后一种方法应用于OpenPET图像重建的方法，并将其与ML-EM方法进行了比较。我们发现，本文提出的分析方法可以减少由于频率丢失造成的图像伪影的发生。这种恢复效果在ML-EM图像重建中也观察到了类似的趋势，其中不应用额外的恢复方法。因此，我们得出结论，凸投影法和ML-EM法在补偿频率损失方面具有相似的恢复效果。
We are developing a new PET scanner based on the “OpenPET” geometry, which consists of two detector rings separated by a gap. One item to which attention must be paid is that OpenPET image reconstruction is classified into an incomplete inverse problem, where low-frequency components are truncated. In our previous simulations and experiments, however, the OpenPET imaging was made feasible by application of iterative image reconstruction methods. Therefore, we expect that iterative methods have a restorative effect to compensate for the lost frequency. There are two types of reconstruction methods for improving image quality when data truncation exists: one is the iterative methods such as the maximum-likelihood expectation maximization (ML-EM) and the other is an analytical image reconstruction method followed by the method of convex projections, which has not been employed for the OpenPET. In this study, therefore, we propose a method for applying the latter approach to the OpenPET image reconstruction and compare it with the ML-EM. We found that the proposed analytical method could reduce the occurrence of image artifacts caused by the lost frequency. A similar tendency for this restoration effect was observed in ML-EM image reconstruction where no additional restoration method was applied. Therefore, we concluded that the method of convex projections and the ML-EM had a similar restoration effect to compensate for the lost frequency.