Sastry S, Carson R E
Physical Sciences Laboratory, Division of Computer Research and Technology, Clinical Center, National Institutes of Health, Bethesda, MD 20892, USA.
IEEE Trans Med Imaging. 1997 Dec;16(6):750-61. doi: 10.1109/42.650872.
The use of anatomical information to improve the quality of reconstructed images in positron emission tomography (PET) has been extensively studied. A common strategy has been to include spatial smoothing within boundaries defined from the anatomical data. We present an alternative method for the incorporation of anatomical information into PET image reconstruction, in which we use segmented magnetic resonance (MR) images to assign tissue composition to PET image pixels. We model the image as a sum of activities for each tissue type, weighted by the assigned tissue composition. The reconstruction is performed as a maximum a posteriori (MAP) estimation of the activities of each tissue type. Two prior functions, defined for tissue-type activities, are considered. The algorithm is tested in realistic simulations employing a full physical model of the PET scanner.
利用解剖学信息来提高正电子发射断层扫描（PET）中重建图像的质量已得到广泛研究。一种常见策略是在根据解剖学数据定义的边界内进行空间平滑处理。我们提出了一种将解剖学信息纳入PET图像重建的替代方法，即使用分割后的磁共振（MR）图像为PET图像像素分配组织成分。我们将图像建模为每种组织类型的活度之和，并由分配的组织成分加权。重建过程作为每种组织类型活度的最大后验（MAP）估计来执行。考虑了为组织类型活度定义的两个先验函数。该算法在使用PET扫描仪完整物理模型的实际模拟中进行了测试。
