Parker D L
Med Phys. 1982 Mar-Apr;9(2):254-7. doi: 10.1118/1.595078.
The problem of using a divergent fan beam convolution reconstruction algorithm in conjunction with a minimal complete (180 degrees plus the fan angle) data set is reviewed. It is shown that by proper weighting of the initial data set, image quality essentially equivalent to the quality of reconstructions from 360 degrees data sets is obtained. The constraints on the weights are that the sum of the two weights corresponding to the same line-integral must equal one, in regions of no data the weights must equal zero, and the weights themselves as well as the gradient of the weights must be continuous over the full 360 degrees. After weighting the initial data with weights that satisfy these constraints, image reconstruction can be conveniently achieved by using the standard (hardwired if available) convolver and backprojector of the specific scanner.
回顾了将发散扇形束卷积重建算法与最小完整(180度加扇角)数据集结合使用的问题。结果表明,通过对初始数据集进行适当加权,可以获得与360度数据集重建质量基本相当的图像质量。权重的约束条件是,对应于同一条线积分的两个权重之和必须等于1,在无数据区域权重必须等于0,并且权重本身以及权重的梯度在整个360度范围内必须连续。在用满足这些约束的权重对初始数据进行加权之后,可以通过使用特定扫描仪的标准(如有则为硬连线)卷积器和反投影器方便地实现图像重建。