Formiconi A R, Passeri A, Guelfi M R, Masoni M, Pupi A, Meldolesi U, Malfetti P, Calori L, Guidazzoli A
Universita' di Firenze, Department of Clinical Physiopathology (DFC), Florence, Italy.
Int J Med Inform. 1997 Nov;47(1-2):125-38. doi: 10.1016/s1386-5056(97)00089-0.
Data from Single Photon Emission Computed Tomography (SPECT) studies are blurred by inevitable physical phenomena occurring during data acquisition. These errors may be compensated by means of reconstruction algorithms which take into account accurate physical models of the data acquisition procedure. Unfortunately, this approach involves high memory requirements as well as a high computational burden which cannot be afforded by the computer systems of SPECT acquisition devices. In this work the possibility of accessing High Performance Computing and Networking (HPCN) resources through a World Wide Web interface for the advanced reconstruction of SPECT data in a clinical environment was investigated. An iterative algorithm with an accurate model of the variable system response was ported on the Multiple Instruction Multiple Data (MIMD) parallel architecture of a Cray T3D massively parallel computer. The system was accessible even from low cost PC-based workstations through standard TCP/IP networking. A speedup factor of 148 was predicted by the benchmarks run on the Cray T3D. A complete brain study of 30 (64 x 64) slices was reconstructed from a set of 90 (64 x 64) projections with ten iterations of the conjugate gradients algorithm in 9 s which corresponds to an actual speed-up factor of 135. The technique was extended to a more accurate 3D modeling of the system response for a true 3D reconstruction of SPECT data; the reconstruction time of the same data set with this more accurate model was 5 min. This work demonstrates the possibility of exploiting remote HPCN resources from hospital sites by means of low cost workstations using standard communication protocols and an user-friendly WWW interface without particular problems for routine use.
单光子发射计算机断层扫描（SPECT）研究的数据在采集过程中会因不可避免的物理现象而模糊。这些误差可以通过重建算法来补偿，该算法考虑了数据采集过程的精确物理模型。不幸的是，这种方法需要高内存需求以及高计算负担，这是SPECT采集设备的计算机系统无法承受的。在这项工作中，研究了通过万维网接口访问高性能计算和网络（HPCN）资源以在临床环境中对SPECT数据进行高级重建的可能性。一种具有可变系统响应精确模型的迭代算法被移植到Cray T3D大规模并行计算机的多指令多数据（MIMD）并行架构上。即使通过基于标准TCP/IP网络的低成本基于PC的工作站也可以访问该系统。在Cray T3D上运行的基准测试预测加速因子为148。从一组90个（64×64）投影重建了30个（64×64）切片的完整脑部研究，共轭梯度算法进行了十次迭代，用时9秒，这对应于实际加速因子为135。该技术被扩展到对系统响应进行更精确的三维建模，以对SPECT数据进行真正的三维重建；使用这个更精确模型对同一数据集的重建时间为5分钟。这项工作证明了利用低成本工作站通过标准通信协议和用户友好的万维网接口从医院站点利用远程HPCN资源进行常规使用而不会有特别问题的可能性。
