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

机译:单光子发射计算机断层扫描图像的迭代三维期望最大化恢复:在纹状体成像中的应用。

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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.
机译:单光子发射计算机断层扫描成像的空间分辨率差,统计噪声高。结果,减小了小结构的对比度,限制了缺陷的视觉检测并且难以精确定量。为了提高对比度,可以将检测系统的空间变异点扩展函数包括在迭代重建算法中。众所周知,这种方法是有效的,但是很耗时。我们基于重建后的恢复方法,开发了一种更快的方法来解决三维空间分辨率损失。该方法使用两个步骤。首先,执行未校正的迭代有序子集期望最大化(OSEM)重建,然后在第二步中,完成重建体积的三维(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(两项模拟和一项实验数据)中与标准OSEM-3D方法进行了比较。在前两个研究中,研究了对比度,噪声和缺陷的视觉检测。在第三项研究中,根据填充了123-I的拟人纹状体幻影获得的数据进行了定量分析。通过仿真,我们证明,对于OSEM-3D和OSEM-R方法,对比度作为噪声和病变可检测性的函数非常相似。在实验研究中,我们获得了大脑不同区域的活动量化比率非常相似的值。与OSEM-3D相比,OSEM-R的优势在于可大幅提高处理时间。该增益取决于几个因素。在典型情况下,对于128 x 128的120个投影采集,OSEM-R比OSEM-3D快13或25倍,具体取决于迭代恢复中使用的计算方法。在本文中,以近似于深度的独立分辨率对OSEM-R方法进行了测试。对于纹状体而言,这种近似是合适的,但是对于其他临床情况,我们将需要包括空间变化的响应。这样的响应已经包含在OSEM-3D中。

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