...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Physics in medicine and biology. >Clinical implementation of a GPU-based simplified Monte Carlo method for a treatment planning system of proton beam therapy.
【24h】

Clinical implementation of a GPU-based simplified Monte Carlo method for a treatment planning system of proton beam therapy.

机译：基于GPU的简化蒙特卡罗方法的临床实施，用于质子束治疗的治疗计划系统。

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

We implemented the simplified Monte Carlo (SMC) method on graphics processing unit (GPU) architecture under the computer-unified device architecture platform developed by NVIDIA. The GPU-based SMC was clinically applied for four patients with head and neck, lung, or prostate cancer. The results were compared to those obtained by a traditional CPU-based SMC with respect to the computation time and discrepancy. In the CPU- and GPU-based SMC calculations, the estimated mean statistical errors of the calculated doses in the planning target volume region were within 0.5% rms. The dose distributions calculated by the GPU- and CPU-based SMCs were similar, within statistical errors. The GPU-based SMC showed 12.30-16.00 times faster performance than the CPU-based SMC. The computation time per beam arrangement using the GPU-based SMC for the clinical cases ranged 9-67 s. The results demonstrate the successful application of the GPU-based SMC to a clinical proton treatment planning.
机译：在由NVIDIA开发的计算机统一设备架构平台下，我们在图形处理单元（GPU）架构上实施了简化的蒙特卡罗（SMC）方法。 基于GPU的SMC在临床上申请了四名头部和颈部，肺或前列腺癌的患者。 将结果与由传统的CPU基SMC获得的结果进行比较，相对于计算时间和差异。 在基于CPU和GPU的SMC计算中，规划目标体积区域中计算剂量的估计平均统计误差在0.5％范内。 由GPU和CPU的SMC计算的剂量分布在统计误差中类似。 基于GPU的SMC显示出比基于CPU的SMC更快的性能更快12.30-16.00倍。 使用基于GPU的SMC进行临床情况的每个波束布置的计算时间范围为9-67秒。 结果证明了基于GPU的SMC对临床质子治疗计划的成功应用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号