{"title":"Technical note: A GPU-based shared Monte Carlo method for fast photon transport in multi-energy x-ray exposures","authors":"Yiwen Zhou, Wenxin Deng, Jing Kang, Jinqiu Xia, Yingjie Yang, Bin Li, Yuqin Zhang, Hongliang Qi, WangJiang Wu, Mengke Qi, Linghong Zhou, Jianhui Ma, Yuan Xu","doi":"10.1002/mp.17314","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>The Monte Carlo (MC) method is an accurate technique for particle transport calculation due to the precise modeling of physical interactions. Nevertheless, the MC method still suffers from the problem of expensive computational cost, even with graphics processing unit (GPU) acceleration. Our previous works have investigated the acceleration strategies of photon transport simulation for single-energy CT. But for multi-energy CT, conventional individual simulation leads to unnecessary redundant calculation, consuming more time.</p>\n </section>\n \n <section>\n \n <h3> Purpose</h3>\n \n <p>This work proposes a novel GPU-based shared MC scheme (gSMC) to reduce unnecessary repeated simulations of similar photons between different spectra, thereby enhancing the efficiency of scatter estimation in multi-energy x-ray exposures.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>The shared MC method selects shared photons between different spectra using two strategies. Specifically, we introduce spectral region classification strategy to select photons with the same initial energy from different spectra, thus generating energy-shared photon groups. Subsequently, the multi-directional sampling strategy is utilized to select energy-and-direction-shared photons, which have the same initial direction, from energy-shared photon groups. Energy-and-direction-shared photons perform shared simulations, while others are simulated individually. Finally, all results are integrated to obtain scatter distribution estimations for different spectral cases.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>The efficiency and accuracy of the proposed gSMC are evaluated on the digital phantom and clinical case. The experimental results demonstrate that gSMC can speed up the simulation in the digital case by ∼37.8% and the one in the clinical case by ∼20.6%, while keeping the differences in total scatter results within 0.09%, compared to the conventional MC package, which performs an individual simulation.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>The proposed GPU-based shared MC simulation method can achieve fast photon transport calculation for multi-energy x-ray exposures.</p>\n </section>\n </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8390-8398"},"PeriodicalIF":3.2000,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical physics","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/mp.17314","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
Background
The Monte Carlo (MC) method is an accurate technique for particle transport calculation due to the precise modeling of physical interactions. Nevertheless, the MC method still suffers from the problem of expensive computational cost, even with graphics processing unit (GPU) acceleration. Our previous works have investigated the acceleration strategies of photon transport simulation for single-energy CT. But for multi-energy CT, conventional individual simulation leads to unnecessary redundant calculation, consuming more time.
Purpose
This work proposes a novel GPU-based shared MC scheme (gSMC) to reduce unnecessary repeated simulations of similar photons between different spectra, thereby enhancing the efficiency of scatter estimation in multi-energy x-ray exposures.
Methods
The shared MC method selects shared photons between different spectra using two strategies. Specifically, we introduce spectral region classification strategy to select photons with the same initial energy from different spectra, thus generating energy-shared photon groups. Subsequently, the multi-directional sampling strategy is utilized to select energy-and-direction-shared photons, which have the same initial direction, from energy-shared photon groups. Energy-and-direction-shared photons perform shared simulations, while others are simulated individually. Finally, all results are integrated to obtain scatter distribution estimations for different spectral cases.
Results
The efficiency and accuracy of the proposed gSMC are evaluated on the digital phantom and clinical case. The experimental results demonstrate that gSMC can speed up the simulation in the digital case by ∼37.8% and the one in the clinical case by ∼20.6%, while keeping the differences in total scatter results within 0.09%, compared to the conventional MC package, which performs an individual simulation.
Conclusions
The proposed GPU-based shared MC simulation method can achieve fast photon transport calculation for multi-energy x-ray exposures.
背景:蒙特卡洛(Monte Carlo,MC)方法对物理相互作用进行了精确建模,是一种精确的粒子传输计算技术。然而,即使使用图形处理器(GPU)加速,MC 方法仍然存在计算成本昂贵的问题。我们之前的工作研究了单能量 CT 的光子传输模拟加速策略。目的:本研究提出了一种新颖的基于 GPU 的共享 MC 方案(gSMC),以减少不同光谱间类似光子不必要的重复模拟,从而提高多能 X 射线曝光中散射估计的效率:共享 MC 方法使用两种策略在不同光谱之间选择共享光子。具体来说,我们引入光谱区域分类策略,从不同光谱中选择初始能量相同的光子,从而生成能量共享光子组。随后,我们利用多方向采样策略,从能量共享光子组中选择初始方向相同的能量和方向共享光子。能量和方向共享光子进行共享模拟,其他光子则单独模拟。最后,综合所有结果,得出不同光谱情况下的散射分布估计值:结果:在数字模型和临床病例上对所提出的 gSMC 的效率和准确性进行了评估。实验结果表明,与执行单个仿真的传统 MC 软件包相比,gSMC 可将数字模型的仿真速度提高 ∼ 37.8%,将临床模型的仿真速度提高 ∼ 20.6%,同时将总散射结果的差异控制在 0.09% 以内:结论:所提出的基于 GPU 的共享 MC 仿真方法可以实现多能量 X 射线照射的快速光子传输计算。
期刊介绍:
Medical Physics publishes original, high impact physics, imaging science, and engineering research that advances patient diagnosis and therapy through contributions in 1) Basic science developments with high potential for clinical translation 2) Clinical applications of cutting edge engineering and physics innovations 3) Broadly applicable and innovative clinical physics developments
Medical Physics is a journal of global scope and reach. By publishing in Medical Physics your research will reach an international, multidisciplinary audience including practicing medical physicists as well as physics- and engineering based translational scientists. We work closely with authors of promising articles to improve their quality.