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

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