Denoising of electron beam Monte Carlo dose distributions using digital filtering techniques.
Denoising of electron beam Monte Carlo dose distributions using digital filtering techniques.
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DOI：
10.1088/0031-9155/45/7/305
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发表时间：
2000-07
影响因子：
3.5
通讯作者：
Joseph O. Deasy
中科院分区：
文献类型：
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作者：
Joseph O. Deasy
蒙特卡罗（MC）方法一直被认为是最终的剂量分布计算技术。然而，固有的随机剂量波动（即噪声）有几个重要的缺点：噪声将影响所有相关的剂量测定和放射生物学指标的估计，噪声将降低由此产生的剂量轮廓可视化。我们建议使用后处理去噪步骤来减少统计波动，并改善剂量轮廓可视化。我们报告的结果应用四种不同的二维数字平滑滤波器的二维剂量图像。集成Tiger系列MC代码用于在两个不同的体模中产生不同深度的10 MeV电子束剂量分布。观察到的滤波的定性效果包括：（a）体素到体素（高频）噪声的抑制和（B）所得到的轮廓图在视觉上更容易理解。在某些情况下，缺点包括表面附近半影的轻微模糊和其他非常清晰的真实的剂量测定特征的轻微模糊。在这里考虑的四个数字滤波器，一个，一个基于局部最小二乘原理的滤波器，出现抑制噪声与真实的剂量测定功能可以忽略不计的退化。我们得出结论，去噪的电子束MC剂量分布是可行的，将产生更好的剂量可靠性和更好的可视化剂量分布。
The Monte Carlo (MC) method has long been viewed as the ultimate dose distribution computational technique. The inherent stochastic dose fluctuations (i.e. noise), however, have several important disadvantages: noise will affect estimates of all the relevant dosimetric and radiobiological indices, and noise will degrade the resulting dose contour visualizations. We suggest the use of a post-processing denoising step to reduce statistical fluctuations and also improve dose contour visualization. We report the results of applying four different two-dimensional digital smoothing filters to two-dimensional dose images. The Integrated Tiger Series MC code was used to generate 10 MeV electron beam dose distributions at various depths in two different phantoms. The observed qualitative effects of filtering include: (a) the suppression of voxel-to voxel (high-frequency) noise and (b) the resulting contour plots are visually more comprehensible. Drawbacks include, in some cases, slight blurring of penumbra near the surface and slight blurring of other very sharp real dosimetric features. Of the four digital filters considered here, one, a filter based on a local least-squares principle, appears to suppress noise with negligible degradation of real dosimetric features. We conclude that denoising of electron beam MC dose distributions is feasible and will yield improved dosimetric reliability and improved visualization of dose distributions.