基于遗传算法的医用直线加速器光子能谱重建方法

Reconstruction method of photon spectra of medical linear accelerator based on genetic algorithm

基于光子束中轴百分深度剂量(PDD),探讨研究了基于遗传算法的医用直线加速器光能能谱精确重建方法.首先,利用蒙特卡洛模拟仿真医用直线加速器治疗头,获得6 MeV光子束的模拟能谱以及单能光子中轴PDD数据;然后,根据测量得到的中轴PDD数据以及模拟得到的单能光子中轴PDD数据,运用遗传算法优化求解重建光子能谱.实验结果表明:重建能谱与蒙特卡洛模拟得到的能谱具有良好的一致性,平均相对误差为3.03%;根据重建能谱计算得到的中轴PDD数据与测量得到的中轴PDD数据之间的平均相对误差为1.0%,与蒙特卡洛模拟得到的中轴PDD数据之间的平均相对误差为2.0%.由此可见,利用所提方法进行光子束能谱重建可靠有效.

A method for precise reconstruction of photon spectra of medical linear accelerator based on genetic algorithm was investigated according to percentage depth dose（PDD） data of photon beam central axis.First,the spectra of 6 MeV photon beams and PDD data of mono-energetic photon beams were calculated by Monte Carlo simulation of accelerator treatment head.Then,the genetic algorithm was employed to reconstruct photon spectra according to both measured and simulated PDD data.The experimental results show that the reconstructed spectra is in good agreement with that calculated by Monte Carlo simulation,the average relative error being 3.03%.The derived PDD data calculated from the reconstructed spectra agree well with both measured and Monte Carlo simulated PDD data,and the average relative errors are 1.0% and 2.0%,respectively.Therefore,the proposed method is reliable and effective for photon spectra reconstruction.