Peter J, Tornai M P, Jaszczek R J
Duke University Medical Center, Durham, NC 27710, USA.
IEEE Trans Med Imaging. 2000 May;19(5):556-64. doi: 10.1109/42.870266.
Monte Carlo simulations in nuclear medicine, with accurately modeled photon transport and high-quality random number generators, require precisely defined and often detailed phantoms as an important component in the simulation process. Contemporary simulation models predominantly employ voxel-driven algorithms, but analytical models offer important advantages. We discuss the implementation of ray-solid intersection algorithms in analytical superquadric-based complex phantoms with additional speed-up rejection testing for use in nuclear medicine imaging simulations, and we make comparisons with voxelized counterparts. Comparisons are made with well-known cold rod:sphere and anthropomorphic phantoms. For these complex phantoms, the analytical phantom representations are nominally several orders of magnitude smaller in memory requirements than are voxelized versions. Analytical phantoms facilitate constant distribution parameters. As a consequence of discretizing a continuous surface into finite bins, for example, time-dependent voxelized phantoms can have difficulties preserving accurate volumes of a beating heart. Although virtually no inaccuracy is associated with path calculations in analytical phantoms, the discretization can negatively impact the simulation process and results. Discretization errors are apparent in reconstructed images of cold rod:sphere voxel-based phantoms because of a redistribution of the count densities in the simulated objects. These problems are entirely avoided in analytical phantoms. Voxelized phantoms can accurately model detailed human shapes based on segmented computed tomography (CT) or magnetic resonance imaging (MRI) images, but analytical phantoms offer advantages in time and accuracy for evaluation and investigation of imaging physics and reconstruction algorithms in a straightforward and efficient manner.
在核医学中，蒙特卡罗模拟需要精确建模的光子传输和高质量的随机数生成器，这就要求在模拟过程中使用精确定义且通常很详细的体模作为重要组成部分。当代模拟模型主要采用体素驱动算法，但解析模型具有重要优势。我们讨论了基于解析超二次曲面的复杂体模中光线 - 实体相交算法的实现，并附加了加速拒绝测试，用于核医学成像模拟，同时与体素化的对应模型进行比较。与著名的冷棒：球体和人体模型进行了比较。对于这些复杂体模，解析体模表示在内存需求上比体素化版本名义上小几个数量级。解析体模便于设置恒定的分布参数。例如，由于将连续表面离散化为有限的单元，随时间变化的体素化体模在保留跳动心脏的准确体积时可能会遇到困难。尽管解析体模中的路径计算几乎没有不准确性，但离散化可能会对模拟过程和结果产生负面影响。在基于冷棒：球体体素的体模的重建图像中，离散化误差很明显，这是由于模拟对象中计数密度的重新分布。而解析体模完全避免了这些问题。体素化体模可以基于分割的计算机断层扫描（CT）或磁共振成像（MRI）图像准确地模拟详细的人体形状，但解析体模在时间和准确性方面具有优势，能够以直接有效的方式评估和研究成像物理和重建算法。
