Dept. of Electr. Eng., Washington Univ., St. Louis, MO.
IEEE Trans Med Imaging. 1993;12(1):84-9. doi: 10.1109/42.222671.
Single photon emission computed tomography (SPECT) reconstructions performed using maximum a posteriori (penalized likelihood) estimation with the expectation maximization algorithm are discussed. Due to the large number of computations, the algorithms were performed on a massively parallel single-instruction multiple-data computer. Computation times for 200 iterations, using I.J. Good and R.A. Gaskins's (1971) roughness as a rotationally invariant roughness penalty, are shown to be on the order of 5 min for a 64x64 image with 96 view angles on an AMT-DAP 4096 processor machine and 1 min on a MasPar 4096 processor machine. Computer simulations performed using parameters for the Siemens gamma camera and clinical brain scan parameters are presented to compare two regularization techniques-regularization by kernel sieves and penalized likelihood with Good's rotationally invariant roughness measure-to filtered backprojection. Twenty-five independent sets of data are reconstructed for the pie and Hoffman brain phantoms. The average variance and average deviation are examined in various areas of the brain phantom. It is shown that while the geometry of the area examined greatly affects the observed results, in all cases the reconstructions using Good's roughness give superior variance and bias results to the two alternative methods.
讨论了使用最大后验（惩罚似然）估计和期望最大化算法进行单光子发射计算机断层扫描（SPECT）重建。由于计算量很大，因此在大规模并行单指令多数据计算机上执行了这些算法。使用 I.J. Good 和 R.A. Gaskins（1971）的粗糙度作为旋转不变的粗糙度惩罚，对于具有 96 个视场角的 64x64 图像，在 AMT-DAP 4096 处理器机器上的计算时间约为 5 分钟，在 MasPar 4096 处理器机器上的计算时间约为 1 分钟。为了比较两种正则化技术——核筛正则化和具有 Good 旋转不变粗糙度度量的惩罚似然——与滤波反投影，使用西门子伽马相机和临床脑扫描参数进行了计算机模拟。对于饼和 Hoffman 脑模型，重建了 25 组独立数据集。在脑模型的各个区域检查了平均方差和平均偏差。结果表明，虽然所检查区域的几何形状极大地影响了观察到的结果，但在所有情况下，使用 Good 的粗糙度进行的重建都比两种替代方法具有更好的方差和偏差结果。
