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Parallel computing methods for X-ray cone beam tomography with large array sizes

机译:具有大型阵列尺寸的X射线锥形断层扫描的并行计算方法

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Cone beam geometries are increasingly of interest for X-ray CT applications to improve imaging efficiency. In this paper, we describe our practical experience implementing circular orbit cone beam backprojection on workstation clusters. The reconstruction problem is computationally intensive, particularly for arrays of 512 voxels in each direction. A voxel driven approach is described where the reconstruction volume is partitioned into variable width slabs and each slab given to a workstation. Each projection is filtered by one workstation and then sent to the others for backprojection. While most computation is done in the backprojection step, a significant amount of time must be spent in sending projectional data. A method is detailed to further reduce the communication overhead by restricting the amount of projection sent to only what is required by each backprojecting workstation. Furthermore, if the shape of the backprojection slabs is made as square as possible, the total communication requirement can be minimized. By reduction of the communication requirement, an overall improvement in processor utilization was observed, and the crossover point where communication dominates was improved.
机译:X射线CT应用越来越感兴趣的锥形束几何形象以提高成像效率。在本文中,我们描述了在工作站集群上实施圆形轨道梁反射的实际经验。重建问题是计算密集的,特别是对于每个方向的512个体素数阵列。描述了体素驱动方法,其中重建体积被划分为可变宽度板和给予工作站的每个板块。每个投影由一个工作站过滤,然后发送给其他项目以进行反投影。虽然大多数计算在反冲步骤中完成,但必须在发送投影数据时花费大量时间。详细说明方法,以通过限制仅发送到每个反射工作站所需的投影量来进一步降低通信开销。此外,如果背分注入板的形状尽可能地作为正方形,则可以最小化总通信要求。通过减少通信要求,观察到处理器利用的总体改进,并且改善了通信主导的交叉点。

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