创建了一种比 OSEM法更快收敛的、更灵活地适应临床要求的医学图象重建迭代算法 .通过引入超松弛因子 z改进现有的 OSEM图象迭代重建算法 ,在 z=1时 ,回复为通常的 OSEM,在 z>1时 ,合并引入非负约束和总计数归一化约束条件 ,保证迭代快速收敛 .使用计算机模拟数据和 SPECT心肌灌注投影数据对该算法进行验证 ,并同其他图象重建算法的结果进行了比较 ,该算法运算速度比同阶数的 OSEM快 1倍以上 ,且比同样迭代次数的更高阶数的 OSEM运算速度还要快 .该算法具有收敛速度快 ,使用灵活等优点 .

An improved OSEM(ordered subset expectation maximization) reconstruction algorithm with OR(overrelaxation) parameter is studied in order to provide a more rapid and practical convergent iterative reconstruction algorithm in tomograph of nuclear medicine, such as SPECT(single photon emission computed tomograph) and PET(positron emission tomograph). Based on the additive version of OSEM, the new method introduces a constant overrelaxation parameter z>1 during each sub-iteration, and imposes the non-negativity constrain and total-counts normalization condition in subset iteration to overcome the negative image value problem and total-counts shift, in order to ensure its rapid and stable convergence. The method is reduced into ordinary OSEM when z=1. The reconstructed images were compared with those of standard OSEM, by both simulated phantom data and clinical SPECT myocardial perfusion data. The OR-OSEM is shown to be one time faster than OSEM's with same subset level, and is even faster than the OSEM with higher subset level. The results also show that this OR-OSEM method is more flexible in practice due to its continuous adjustable OR parameter.