Suppr超能文献

英伟达OptiX光线追踪引擎作为医学成像系统建模的新工具。

NVIDIA OptiX ray-tracing engine as a new tool for modelling medical imaging systems.

作者信息

Pietrzak Jakub, Kacperski Krzysztof, Cieślar Marek

机构信息

The Maria Skłodowska - Curie Memorial Cancer Centre and Institute of Oncology, Warsaw, Poland.

University of Warsaw, Faculty of Physics, Warsaw, Poland.

出版信息

Proc SPIE Int Soc Opt Eng. 2015 Mar 18;9412. doi: 10.1117/12.2082349.

Abstract

The most accurate technique to model the X- and gamma radiation path through a numerically defined object is the Monte Carlo simulation which follows single photons according to their interaction probabilities. A simplified and much faster approach, which just integrates total interaction probabilities along selected paths, is known as ray tracing. Both techniques are used in medical imaging for simulating real imaging systems and as projectors required in iterative tomographic reconstruction algorithms. These approaches are ready for massive parallel implementation e.g. on Graphics Processing Units (GPU), which can greatly accelerate the computation time at a relatively low cost. In this paper we describe the application of the NVIDIA OptiX ray-tracing engine, popular in professional graphics and rendering applications, as a new powerful tool for X- and gamma ray-tracing in medical imaging. It allows the implementation of a variety of physical interactions of rays with pixel-, mesh- or nurbs-based objects, and recording any required quantities, like path integrals, interaction sites, deposited energies, and others. Using the OptiX engine we have implemented a code for rapid Monte Carlo simulations of Single Photon Emission Computed Tomography (SPECT) imaging, as well as the ray-tracing projector, which can be used in reconstruction algorithms. The engine generates efficient, scalable and optimized GPU code, ready to run on multi GPU heterogeneous systems. We have compared the results our simulations with the GATE package. With the OptiX engine the computation time of a Monte Carlo simulation can be reduced from days to minutes.

摘要

对穿过数值定义对象的X射线和伽马射线路径进行建模的最准确技术是蒙特卡罗模拟,它根据单光子的相互作用概率追踪单个光子。一种简化且速度快得多的方法,即仅沿选定路径对总相互作用概率进行积分,被称为光线追踪。这两种技术都用于医学成像,以模拟真实成像系统,并作为迭代断层重建算法所需的投影仪。这些方法已准备好大规模并行实现,例如在图形处理单元(GPU)上,这可以以相对较低的成本大大加快计算时间。在本文中,我们描述了在专业图形和渲染应用中流行的NVIDIA OptiX光线追踪引擎作为医学成像中X射线和伽马射线追踪的一种新的强大工具的应用。它允许实现光线与基于像素、网格或非均匀有理B样条曲线(NURBS)的对象的各种物理相互作用,并记录任何所需的量,如路径积分、相互作用位点、沉积能量等。使用OptiX引擎,我们实现了一个用于单光子发射计算机断层扫描(SPECT)成像快速蒙特卡罗模拟的代码,以及可用于重建算法的光线追踪投影仪。该引擎生成高效、可扩展且经过优化的GPU代码,准备好在多GPU异构系统上运行。我们将模拟结果与GATE软件包进行了比较。使用OptiX引擎,蒙特卡罗模拟的计算时间可以从数天减少到数分钟。

相似文献

1
NVIDIA OptiX ray-tracing engine as a new tool for modelling medical imaging systems.
Proc SPIE Int Soc Opt Eng. 2015 Mar 18;9412. doi: 10.1117/12.2082349.
2
Hybrid framework for feasible modeling of an edge illumination X-ray phase-contrast imaging system at a human scale.
Phys Med. 2017 Aug;40:1-10. doi: 10.1016/j.ejmp.2017.05.067. Epub 2017 Jul 17.
5
CAD-ASTRA: a versatile and efficient mesh projector for X-ray tomography with the ASTRA-toolbox.
Opt Express. 2024 Jan 29;32(3):3425-3439. doi: 10.1364/OE.498194.
6
A GPU OpenCL based cross-platform Monte Carlo dose calculation engine (goMC).
Phys Med Biol. 2015 Oct 7;60(19):7419-35. doi: 10.1088/0031-9155/60/19/7419. Epub 2015 Sep 9.
7
Efficient simulation of voxelized phantom in GATE with embedded SimSET multiple photon history generator.
Phys Med Biol. 2014 Oct 21;59(20):6231-50. doi: 10.1088/0031-9155/59/20/6231. Epub 2014 Sep 26.
8
GMC: a GPU implementation of a Monte Carlo dose calculation based on Geant4.
Phys Med Biol. 2012 Mar 7;57(5):1217-29. doi: 10.1088/0031-9155/57/5/1217. Epub 2012 Feb 14.
9
Geant4-based Monte Carlo simulations on GPU for medical applications.
Phys Med Biol. 2013 Aug 21;58(16):5593-611. doi: 10.1088/0031-9155/58/16/5593. Epub 2013 Jul 29.

本文引用的文献

1
GPU computing in medical physics: a review.
Med Phys. 2011 May;38(5):2685-97. doi: 10.1118/1.3578605.
2
GATE: a simulation toolkit for PET and SPECT.
Phys Med Biol. 2004 Oct 7;49(19):4543-61. doi: 10.1088/0031-9155/49/19/007.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验