Monte Carlo reference data sets for imaging research: Executive summary of the report of AAPM Research Committee Task Group 195
Monte Carlo reference data sets for imaging research: Executive summary of the report of AAPM Research Committee Task Group 195
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DOI：
10.1118/1.4928676
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发表时间：
2015-10-01
期刊：
影响因子：
3.8
通讯作者：
Turner, Adam C.
中科院分区：
文献类型：
--
作者：
Sechopoulos, Ioannis;Ali, Elsayed S. M.;Turner, Adam C.
蒙特卡罗模拟在诊断医学成像研究中的应用是广泛的，因为它的灵活性和估计量的能力是具有挑战性的经验测量。但是，任何新的蒙特卡罗模拟代码都需要经过验证才能可靠地使用。所需验证的类型和程度取决于研究项目的目标，但是，通常情况下，这种验证涉及将模拟结果与物理测量结果或与先前发表的用已建立的蒙特卡罗代码获得的结果进行比较。前者是复杂的，由于实验条件和不确定性的细微差别，而后者是具有挑战性的，由于典型的图形表示和缺乏模拟细节在以前的出版物。此外，进入蒙特卡罗模拟领域通常涉及一个陡峭的学习曲线。学习如何编程和解释蒙特卡罗模拟并不是一项简单的任务，即使使用公开可用的代码包之一也是如此。本任务组报告为在一系列蒙特卡罗代码和模拟场景中对蒙特卡罗模拟进行基准测试提供了一个通用参考。在报告中，提供了涉及常见x射线成像研究领域的六种不同的蒙特卡罗模拟案例的所有模拟条件。使用四个公开的蒙特卡罗软件包对六个病例获得的结果以表格形式列示。除了对所有模拟条件和结果的完整描述之外，还包括对蒙特卡罗包之间结果的讨论和比较以及在编译这些结果期间获得的经验教训。本报告的节略本只包括对六个案件的介绍性说明和其中一个案件的结果的简要示例。这项工作为研究者提供了必要的信息，以便在执行他/她自己的新研究之前，根据这里包含的参考案例对他/她的蒙特卡罗模拟软件进行基准测试。此外，进入蒙特卡罗模拟领域的研究者可以使用这些描述和结果作为自学工具，以确保他/她能够正确地执行特定的模拟。最后，教育工作者可以将这些案例分配为学习项目，作为课程目标或培训计划的一部分。(C) 2015年美国医学物理学家协会。
The use of Monte Carlo simulations in diagnostic medical imaging research is widespread due to its flexibility and ability to estimate quantities that are challenging to measure empirically. However, any new Monte Carlo simulation code needs to be validated before it can be used reliably. The type and degree of validation required depends on the goals of the research project, but, typically, such validation involves either comparison of simulation results to physical measurements or to previously published results obtained with established Monte Carlo codes. The former is complicated due to nuances of experimental conditions and uncertainty, while the latter is challenging due to typical graphical presentation and lack of simulation details in previous publications. In addition, entering the field of Monte Carlo simulations in general involves a steep learning curve. It is not a simple task to learn how to program and interpret a Monte Carlo simulation, even when using one of the publicly available code packages. This Task Group report provides a common reference for benchmarking Monte Carlo simulations across a range of Monte Carlo codes and simulation scenarios. In the report, all simulation conditions are provided for six different Monte Carlo simulation cases that involve common x-ray based imaging research areas. The results obtained for the six cases using four publicly available Monte Carlo software packages are included in tabular form. In addition to a full description of all simulation conditions and results, a discussion and comparison of results among the Monte Carlo packages and the lessons learned during the compilation of these results are included. This abridged version of the report includes only an introductory description of the six cases and a brief example of the results of one of the cases. This work provides an investigator the necessary information to benchmark his/her Monte Carlo simulation software against the reference cases included here before performing his/her own novel research. In addition, an investigator entering the field of Monte Carlo simulations can use these descriptions and results as a self-teaching tool to ensure that he/she is able to perform a specific simulation correctly. Finally, educators can assign these cases as learning projects as part of course objectives or training programs. (C) 2015 American Association of Physicists in Medicine.