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首页> 外文期刊>IEEE Transactions on Medical Imaging >Performance characteristics of the 3-D OSEM algorithm in the reconstruction of small animal PET images
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Performance characteristics of the 3-D OSEM algorithm in the reconstruction of small animal PET images

机译:3-D OSEM算法在小动物PET图像重建中的性能特征

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摘要

Rat brain images acquired with a small animal positron emission tomography (PET) camera and reconstructed with the three-dimensional (3-D) ordered-subsets expectation-maximization (OSEM) algorithm with resolution recovery have better quality when the brain is imaged by itself than when inside the head with surrounding background activity. The purpose of this study was to characterize the dependence of this effect on the level of background activity, attenuation, and scatter. Monte Carlo simulations of the imaging system were performed. The coefficient of variation from replicate images, full-width at half-maximum (FWHM) from point sources and image profile fitting, and image contrast and uniformity were used to evaluate algorithm performance. A rat head with the typical levels of five and ten times the brain activity in the surrounding background requires additional iterations to achieve the same resolution as the brain-only case at a cost of 24% and 64% additional noise, respectively. For the same phantoms, object scatter reduced contrast by 3%-5%. However, attenuation degraded resolution by 0.2 mm and was responsible for up to 12% nonuniformity in the brain images suggesting that attenuation correction is useful. Given the effects of emission and attenuation distribution on both resolution and noise, simulations or phantom studies should be used for each imaging situation to select the appropriate number of OSEM iterations to achieve the desired resolution-noise levels.
机译:使用小型动物正电子发射断层扫描(PET)相机获取并使用具有分辨率恢复功能的三维(3-D)有序子集期望最大化(OSEM)算法重建的大鼠脑图像,其自身成像时具有更好的质量而不是在头部周围进行背景活动时。这项研究的目的是表征这种效应对背景活性,衰减和散射水平的依赖性。进行了成像系统的蒙特卡洛模拟。重复图像的变异系数,点源的半峰全宽(FWHM)和图像轮廓拟合以及图像对比度和均匀性用于评估算法性能。在周围背景中,具有典型水平五倍和十倍大脑活动水平的大鼠头部需要额外的迭代才能获得与仅大脑情况相同的分辨率,但分别需要增加24%和64%的噪音。对于相同的体模,对象散射使对比度降低了3%-5%。但是,衰减会使分辨率降低0.2 mm,并导致大脑图像中的不均匀性高达12%,这表明衰减校正是有用的。考虑到发射和衰减分布对分辨率和噪声的影响,应针对每种成像情况使用仿真或幻像研究,以选择适当数量的OSEM迭代以实现所需的分辨率噪声水平。

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