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单光子发射计算机断层扫描图像的迭代三维期望最大化重建:在纹状体成像中的应用

Iterative three-dimensional expectation maximization restoration of single photon emission computed tomography images: application in striatal imaging.

作者信息

Gantet Pierre, Payoux Pierre, Celler Anna, Majorel Cynthia, Gourion Daniel, Noll Dominikus, Esquerré Jean-Paul

机构信息

Laboratoire de Biophysique EA3033, Université Paul Sabatier Toulouse, France.

出版信息

Med Phys. 2006 Jan;33(1):52-60. doi: 10.1118/1.2135908.

Abstract

Single photon emission computed tomography imaging suffers from poor spatial resolution and high statistical noise. Consequently, the contrast of small structures is reduced, the visual detection of defects is limited and precise quantification is difficult. To improve the contrast, it is possible to include the spatially variant point spread function of the detection system into the iterative reconstruction algorithm. This kind of method is well known to be effective, but time consuming. We have developed a faster method to account for the spatial resolution loss in three dimensions, based on a postreconstruction restoration method. The method uses two steps. First, a noncorrected iterative ordered subsets expectation maximization (OSEM) reconstruction is performed and, in the second step, a three-dimensional (3D) iterative maximum likelihood expectation maximization (ML-EM) a posteriori spatial restoration of the reconstructed volume is done. In this paper, we compare to the standard OSEM-3D method, in three studies (two in simulation and one from experimental data). In the two first studies, contrast, noise, and visual detection of defects are studied. In the third study, a quantitative analysis is performed from data obtained with an anthropomorphic striatal phantom filled with 123-I. From the simulations, we demonstrate that contrast as a function of noise and lesion detectability are very similar for both OSEM-3D and OSEM-R methods. In the experimental study, we obtained very similar values of activity-quantification ratios for different regions in the brain. The advantage of OSEM-R compared to OSEM-3D is a substantial gain of processing time. This gain depends on several factors. In a typical situation, for a 128 x 128 acquisition of 120 projections, OSEM-R is 13 or 25 times faster than OSEM-3D, depending on the calculation method used in the iterative restoration. In this paper, the OSEM-R method is tested with the approximation of depth independent resolution. For the striatum this approximation is appropriate, but for other clinical situations we will need to include a spatially varying response. Such a response is already included in OSEM-3D.

摘要

单光子发射计算机断层扫描成像存在空间分辨率低和统计噪声高的问题。因此,小结构的对比度降低,缺陷的视觉检测受限,精确量化也很困难。为了提高对比度,可以将检测系统的空间变化点扩散函数纳入迭代重建算法。这种方法众所周知是有效的,但耗时较长。我们基于重建后恢复方法开发了一种更快的方法来考虑三维空间分辨率损失。该方法分两步进行。首先,进行未校正的迭代有序子集期望最大化(OSEM)重建,第二步,对重建体积进行三维(3D)迭代最大似然期望最大化(ML-EM)后验空间恢复。在本文中,我们在三项研究(两项模拟研究和一项实验数据研究)中与标准的OSEM-3D方法进行了比较。在前两项研究中,研究了对比度、噪声和缺陷的视觉检测。在第三项研究中,对填充有123-I的拟人化纹状体模型获得的数据进行了定量分析。从模拟结果来看,我们证明OSEM-3D和OSEM-R方法在对比度作为噪声函数以及病变可检测性方面非常相似。在实验研究中,我们在大脑不同区域获得了非常相似的活度定量比值。与OSEM-3D相比,OSEM-R的优势在于处理时间大幅减少。这种减少取决于几个因素。在典型情况下,对于128×128采集120个投影的情况,根据迭代恢复中使用的计算方法,OSEM-R比OSEM-3D快13倍或25倍。在本文中,OSEM-R方法采用深度无关分辨率近似进行测试。对于纹状体,这种近似是合适的,但对于其他临床情况,我们需要纳入空间变化响应。这种响应已包含在OSEM-3D中。

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