Badawi R D, Miller M P, Bailey D L, Marsden P K
Guy's and St Thomas' Clinical PET Centre, Division of Radiological Sciences and Medical Engineering, King's College, London, UK.
Phys Med Biol. 1999 Apr;44(4):941-54. doi: 10.1088/0031-9155/44/4/010.
In positron emission tomography (PET), random coincidence events must be removed from the measured signal in order to obtain quantitatively accurate data. The most widely implemented technique for estimating the number of random coincidences on a particular line of response is the delayed coincidence channel method. Estimates obtained in this way are subject to Poisson noise, which then propagates into the final image when the estimates are subtracted from the prompt signal. However, this noise may be reduced if variance reduction techniques similar to those used in normalization of PET detectors are applied to the randoms estimates prior to use. We have investigated the effects of randoms variance reduction on noise-equivalent count (NEC) rates on a whole-body PET camera operating in 3D mode. NEC rates were calculated using a range of phantoms representative of situations that might be encountered clinically. We have also investigated the properties of three randoms variance reduction methods (based on algorithms previously used for normalization) in terms of their systematic accuracy and their variance reduction efficacy, both in phantom studies and in vivo. Those algorithms investigated that do not make assumptions about the spatial distribution of random coincidences give the best estimates of the randoms distribution. With the camera used, which has a limited axial extent (10.8 cm) and a large ring diameter (102 cm), the gains in image signal-to-noise ratio obtained with this technique ranged from approximately 5% to approximately 15%, depending on object size, activity distribution and the amount of activity in the field of view. Larger gains would be expected if this technique were to be employed on cameras of greater axial extent and smaller ring diameter.
在正电子发射断层扫描（PET）中，为了获得定量准确的数据，必须从测量信号中去除随机符合事件。估计特定响应线上随机符合事件数量的最广泛应用的技术是延迟符合通道法。以这种方式获得的估计值受到泊松噪声的影响，当从即时信号中减去这些估计值时，泊松噪声会传播到最终图像中。然而，如果在使用前将类似于PET探测器归一化中使用的方差减少技术应用于随机事件估计，则可以降低这种噪声。我们研究了在3D模式下运行的全身PET相机上，随机事件方差减少对噪声等效计数（NEC）率的影响。使用一系列代表临床可能遇到情况的体模计算NEC率。我们还在体模研究和体内研究中，从系统准确性和方差减少效果方面，研究了三种随机事件方差减少方法（基于先前用于归一化的算法）的特性。所研究的那些不假设随机符合事件空间分布的算法，能给出随机事件分布的最佳估计。对于所使用的相机，其轴向范围有限（10.8厘米）且环直径较大（102厘米），根据物体大小、活度分布和视野内的活度数量，使用该技术获得的图像信噪比增益范围约为5%至约15%。如果将该技术应用于轴向范围更大且环直径更小的相机，预计会有更大的增益。
