Hamamatsu Photonics K.K., Tokyo.
IEEE Trans Med Imaging. 1992;11(1):21-7. doi: 10.1109/42.126906.
A method for stabilizing iterative image reconstruction techniques has been developed for improving the image quality of position emission tomography. A damping matrix is introduced, which suppresses noisy correction on a pixel-by-pixel basis, depending on the statistical precision of the iterative correction. The precision is evaluated by comparing a certain number of correction submatrices, each of which is formed from a subset of the projection data. Simulation studies showed that statistical noise is effectively suppressed, while the image of the source object is reconstructed with high resolution, as long as the signal level is higher than the local noise level. In the application to the MLE (maximum likelihood estimator), the minimum RMS error of the image was reduced to 84% for 500 k total counts, and the RMS error increased more slowly with further iterations as compared with the simple MLE. The method was also applied to the FIR (filtered iterative reconstruction) algorithm, and the images were found to be better than those obtained by the convolution backprojection method.
已经开发出一种用于稳定迭代图像重建技术的方法，以提高正电子发射断层扫描的图像质量。引入了一个阻尼矩阵，该矩阵根据迭代校正的统计精度，在像素的基础上抑制噪声校正。通过比较一定数量的校正子矩阵来评估精度，每个子矩阵由投影数据的子集形成。模拟研究表明，只要信号水平高于局部噪声水平，就可以有效地抑制统计噪声，同时以高分辨率重建源物体的图像。在应用于最大似然估计 (MLE) 时，对于 500 k 总计数，图像的 RMS 误差最小降低到 84%，与简单 MLE 相比，随着进一步迭代，RMS 误差增加得更慢。该方法还应用于滤波迭代重建 (FIR) 算法，发现重建的图像优于卷积反投影方法获得的图像。
