Accelerating Monte Carlo simulations of radiation therapy dose distributions using wavelet threshold de-noising
Accelerating Monte Carlo simulations of radiation therapy dose distributions using wavelet threshold de-noising
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DOI：
10.1118/1.1508112
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发表时间：
2002-10-01
期刊：
影响因子：
3.8
通讯作者：
Picard, M
中科院分区：
文献类型：
--
作者：
Deasy, JO;Wickerhauser, MV;Picard, M
蒙特卡罗剂量计算方法通过模拟单个高能光子或电子穿过患者解剖结构的数字表示来工作。然而，蒙特卡罗结果波动，直到大量的粒子被模拟。我们建议小波阈值去噪作为后处理步骤，以加速收敛的蒙特卡罗剂量计算。采样粗糙函数（如蒙特卡罗噪声）给出的小波变换系数比采样平滑函数的小波变换系数在幅度上更接近相等。小波硬阈值去噪将低于阈值的小波系数置零，然后重建图像。我们用C语言实现了计算效率高的9，7-双正交滤波器。在变换原点选择上对变换结果取平均值以减少伪影。描述了一种用于选择最佳阈值的方法。该算法需要每个剂量网格点大约336个浮点算术运算。我们应用小波阈值去噪两个二维剂量分布：10 MeV的电子入射到水的幻影与步骤的异质性，从肺异质性幻影切片产生的剂量分布。使用Integrated Tiger Series Monte Carlo代码模拟剂量分布。我们研究了阈值的选择，所产生的剂量图像的平滑度，以及所产生的剂量图像的精度作为源粒子的数量的函数。对于这两个幻影，与一个合适的阈值参数值，体素到体素的噪声被抑制，几乎没有引入的偏见。小波去噪剂量分布的粗糙度（根据拉普拉斯度量）几乎与源电子的数量无关，尽管去噪剂量图像的准确度随着源电子数量的增加而提高。我们得出结论，小波收缩去噪是一种很有前途的方法，有效地加速蒙特卡罗剂量计算的2个或更多的因素。(C)2002年美国医学物理学家协会。
The Monte Carlo dose calculation method works by simulating individual energetic photons or electrons as they traverse a digital representation of the patient anatomy. However, Monte Carlo results fluctuate until a large number of particles are simulated. We propose wavelet threshold de-noising as a postprocessing step to accelerate convergence of Monte Carlo dose calculations. A sampled rough function (such as Monte Carlo noise) gives wavelet transform coefficients which are more nearly equal in amplitude than those of a sampled smooth function. Wavelet hard-threshold de-noising sets to zero those wavelet coefficients which fall below a threshold; the image is then reconstructed. We implemented the computationally efficient 9,7-biorthogonal filters in the C language. Transform results were averaged over transform origin selections to reduce artifacts. A method for selecting best threshold values is described. The algorithm requires about 336 floating point arithmetic operations per dose grid point. We applied wavelet threshold de-noising to two two-dimensional dose distributions: a dose distribution generated by 10 MeV electrons incident on a water phantom with a step-heterogeneity, and a slice from a lung heterogeneity phantom. Dose distributions were simulated using the Integrated Tiger Series Monte Carlo code. We studied threshold selection, resulting dose image smoothness, and resulting dose image accuracy as a function of the number of source particles. For both phantoms, with a suitable value of the threshold parameter, voxel-to-voxel noise was suppressed with little introduction of bias. The roughness of wavelet de-noised dose distributions (according to a Laplacian metric) was nearly independent of the number of source electrons, though the accuracy of the de-noised dose image improved with increasing numbers of source electrons. We conclude that wavelet shrinkage de-noising is a promising method for effectively accelerating Monte Carlo dose calculations by factors of 2 or more. (C) 2002 American Association of Physicists in Medicine.