A parallel Monte Carlo code for planar and SPECT imaging: implementation, verification and applications in (131)I SPECT.
A parallel Monte Carlo code for planar and SPECT imaging: implementation, verification and applications in (131)I SPECT.
复制标题
用于平面和 SPECT 成像的并行蒙特卡罗代码：(131)I SPECT 中的实现、验证和应用。
DOI：
10.1016/s0169-2607(01)00121-3
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发表时间：
2002
影响因子：
6.1
通讯作者：
Koral,KennethF
中科院分区：
文献类型：
--
作者：
Dewaraja,YuniK;Ljungberg,Michael;Majumdar,Amitava;Bose,Abhijit;Koral,KennethF
本文报道了SIMIND蒙特卡罗代码在IBM SP2分布式内存并行计算机上的实现。描述了在并行体系结构上运行蒙特卡罗粒子输运计算的基本方面。我们的并行化基于处理器之间的均匀分配光子，并使用消息传递接口（MPI）库进行处理器间通信，并使用可扩展并行随机数生成器（SPRNG）生成不相关的随机数流。这些并行化技术也适用于其他分布式内存体系结构。对于最多32个处理器，计算速度与处理器数量呈线性增长。这种加速在涉及高能量光子发射器的单光子发射计算机断层扫描（SPECT）模拟中尤其重要，其中需要对幻影和准直器进行明确的建模。对于131i，通过比较模拟和实验的心脏/胸腔幻象的SPECT图像来证明并行代码的准确性。临床逼真的SPECT模拟使用体素-人幻影进行评估散射和衰减校正。
This paper reports the implementation of the SIMIND Monte Carlo code on an IBM SP2 distributed memory parallel computer. Basic aspects of running Monte Carlo particle transport calculations on parallel architectures are described. Our parallelization is based on equally partitioning photons among the processors and uses the Message Passing Interface (MPI) library for interprocessor communication and the Scalable Parallel Random Number Generator (SPRNG) to generate uncorrelated random number streams. These parallelization techniques are also applicable to other distributed memory architectures. A linear increase in computing speed with the number of processors is demonstrated for up to 32 processors. This speed-up is especially significant in Single Photon Emission Computed Tomography (SPECT) simulations involving higher energy photon emitters, where explicit modeling of the phantom and collimator is required. For131I, the accuracy of the parallel code is demonstrated by comparing simulated and experimental SPECT images from a heart/thorax phantom. Clinically realistic SPECT simulations using the voxel-man phantom are carried out to assess scatter and attenuation correction.