锥束CT FDK重建算法的GPU并行实现  

GPU-based parallel implementation of FDK algorithm for cone-beam CT

作　　者：韩玉[1] 闫镔[1] 宇超群[1] 李磊[1] 李建新[1] 

机构地区：[1]信息工程大学信息工程学院,郑州450002

出　　处：《计算机应用》2012年第5期1407-1410,共4页journal of Computer Applications

基　　金：国家863计划项目(2009AA012201)

摘　　要：针对FDK算法重建耗时长的问题,提出了一种基于图形处理器(GPU)的FDK并行加速算法。通过采用合理的线程分配方式,对反投影参数计算过程中与体素无关的中间变量的提取和预计算、对全局存储器访问次数的细致优化等策略,提高FDK算法的执行效率。仿真实验结果表明,在不牺牲重建质量的前提下,完全优化后的FDK并行加速算法重建2563规模的体数据需要0.5 s,重建5123规模的体数据需要2.5 s,这与较新的研究成果相比有很大幅度的提升。To improve the reconstruction speed of the FDK algorithm, this paper presented a fast algorithm based on the graphics processing unit （GPU）. The method acquired higher computational efficiency through more careful optimization techniques, including reasonable mode of thread assigning, collecting and pre-computing the variables which were irrelevant with the voxel and the decreasing of number of global memory accesses. The simulation results show that while the fully optimized algorithm makes no precision reduction, the reconstruction time for 256^3 is only 0.5 seconds and for 512^3 is only 2. 5 seconds, which is a big advance in comparison with the latest research findings.

关 键 词：锥束CT 图像重建 FDK算法 图形处理器 

分 类 号：TP302[自动化与计算机技术—计算机系统结构] TP315[自动化与计算机技术—计算机科学与技术]