Realistic CT simulation using the 4D XCAT phantom
Realistic CT simulation using the 4D XCAT phantom
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DOI：
10.1118/1.2955743
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发表时间：
2008-08-01
期刊：
影响因子：
3.8
通讯作者：
Tsui, B. M. W.
中科院分区：
文献类型：
--
作者：
Segars, W. P.;Mahesh, M.;Tsui, B. M. W.
作者开发了一个独特的CT仿真工具的基础上的4D扩展的心脏躯干（XCAT）的幻影，人体解剖学和生理学的基于NURBS曲面的全身计算机模型。与当前基于简单数学基元的CT体模不同，4D XCAT提供了复杂人体解剖结构的准确表示，并且由于其设计，其器官形状可以改变以逼真地模拟解剖结构变化和患者运动。然而，XCAT的NURBS基础的一个缺点是，曲面的数学复杂性使得通过体模计算线积分变得困难。它们必须使用迭代程序进行计算;因此，CT投影的计算比简单的数学模型慢得多。为了克服这一局限性，作者使用计算机图形学中的有效射线追踪技术，开发了一种快速解析投影算法，以根据XCAT体模的表面定义（给定定义CT扫描仪和几何结构的参数）直接准确计算CT投影。使用此工具，可以在合理的时间内从XCAT模拟和重建逼真的高分辨率3D和4D投影图像。在与其他模拟器与几何定义的器官相比，基于XCAT的算法被发现是只有三倍慢，在使用一个单一的3.2 GHz的处理器生成相同的解剖结构的投影数据集。因此，为了克服这种速度降低，只需要在三个处理器上并行运行投影算法。随着计算机成本的不断降低以及更快的处理器和多处理器系统和集群的兴起，这种放缓基本上是无关紧要的，特别是考虑到XCAT在现实主义和从解剖学上不同的患者生成3D和4D数据的能力方面提供了巨大的改进。因此，作者得出结论，在这项工作中开发的高效的基于XCAT的CT模拟器将在广泛的CT成像研究中应用。(c)2008年美国医学物理学家协会。
The authors develop a unique CT simulation tool based on the 4D extended cardiac-torso (XCAT) phantom, a whole-body computer model of the human anatomy and physiology based on NURBS surfaces. Unlike current phantoms in CT based on simple mathematical primitives, the 4D XCAT provides an accurate representation of the complex human anatomy and has the advantage, due to its design, that its organ shapes can be changed to realistically model anatomical variations and patient motion. A disadvantage to the NURBS basis of the XCAT, however, is that the mathematical complexity of the surfaces makes the calculation of line integrals through the phantom difficult. They have to be calculated using iterative procedures; therefore, the calculation of CT projections is much slower than for simpler mathematical phantoms. To overcome this limitation, the authors used efficient ray tracing techniques from computer graphics, to develop a fast analytic projection algorithm to accurately calculate CT projections directly from the surface definition of the XCAT phantom given parameters defining the CT scanner and geometry. Using this tool, realistic high-resolution 3D and 4D projection images can be simulated and reconstructed from the XCAT within a reasonable amount of time. In comparison with other simulators with geometrically defined organs, the XCAT-based algorithm was found to be only three times slower in generating a projection data set of the same anatomical structures using a single 3.2 GHz processor. To overcome this decrease in speed would, therefore, only require running the projection algorithm in parallel over three processors. With the ever decreasing cost of computers and the rise of faster processors and multi-processor systems and clusters, this slowdown is basically inconsequential, especially given the vast improvement the XCAT offers in terms of realism and the ability to generate 3D and 4D data from anatomically diverse patients. As such, the authors conclude that the efficient XCAT-based CT simulator developed in this work will have applications in a broad range of CT imaging research. (c) 2008 American Association of Physicists in Medicine.