Adaptive anisotropic diffusion filtering of Monte Carlo dose distributions.
The Monte Carlo method is the most accurate method for radiotherapy dose calculations, if used correctly. However, any Monte Carlo dose calculation is burdened with statistical noise. In this paper, denoising of Monte Carlo dose distributions with a three-dimensional adaptive anisotropic diffusion method was investigated. The standard anisotropic diffusion method was extended by changing the filtering parameters adaptively according to the local statistical noise. Smoothing of dose distributions with different noise levels in an inhomogeneous phantom, a conventional and an IMRT treatment case is shown. The resultant dose distributions were analysed using several evaluating criteria. It is shown that the adaptive anisotropic diffusion method can reduce statistical noise significantly (two to five times, corresponding to the reduction of simulation time by a factor of up to 20), while preserving important gradients of the dose distribution well. The choice of free parameters of the method was found to be fairly robust.
D016880:Anisotropy; D003198:Computer Simulation; D004058:Diffusion; D005246:Feedback; D006258:Head and Neck Neoplasms / Q000000981:diagnostic imaging* / Q000503:physiopathology*; D006801:Humans; D008954:Models, Biological; D009010:Monte Carlo Method; D019047:Phantoms, Imaging; D011786:Quality Control; D011874:Radiometry / Q000379:methods*; D011877:Radionuclide Imaging; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D020266:Radiotherapy, Conformal / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013269:Stochastic Processes