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首页> 外文会议>Computational Imaging V; Proceedings of SPIE-The International Society for Optical Engineering; vol.6498; Electronic Imaging Science and Technology >Iterative reconstruction of cone-beam CT data on a cluster
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Iterative reconstruction of cone-beam CT data on a cluster

机译：集群上锥束CT数据的迭代重建

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摘要

Three-dimensional iterative reconstruction of large CT data sets poses several challenges in terms of the associated computational and memory requirements. In this paper, we present results obtained by implementing a computational framework for reconstructing axial cone-beam CT data using a cluster of inexpensive dualprocessor PCs. In particular, we discuss our parallelization approach, which uses POSIX threads and message passing (MPI) for local and remote load distribution, as well as the interaction of that load distribution with the implementation of ordered subset based algorithms. We also consider a heuristic data-driven 3D focus of attention algorithm that reduces the amount of data that must be considered for many data sets. Furthermore, we present a modification to the SIRT algorithm that reduces the amount of data that must be communicated between processes. Finally, we introduce a method of separating the work in such a way that some computation can be overlapped with the MPI communication thus further reducing the overall run-time. We summarize the performance results using reconstructions of experimental data.
机译：大型CT数据集的三维迭代重建在相关的计算和内存需求方面提出了一些挑战。在本文中，我们介绍了通过使用便宜的双处理器PC集群实现用于重建轴向锥束CT数据的计算框架而获得的结果。特别是，我们讨论了并行化方法，该方法将POSIX线程和消息传递（MPI）用于本地和远程负载分配，以及该负载分配与基于有序子集的算法的实现之间的交互。我们还考虑了启发式数据驱动的3D注意算法，该算法减少了许多数据集必须考虑的数据量。此外，我们提出了对SIRT算法的修改，该修改减少了必须在进程之间传递的数据量。最后，我们介绍了一种分离工作的方法，使得一些计算可以与MPI通信重叠，从而进一步减少了总体运行时间。我们使用重建的实验数据总结了性能结果。

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