Photon Energy Spectrum Reconstruction by Several Regression Algorithms in Radiotherapy
To obtain the photon energy spectra of medical accelearator in radiotherapy effectively, a nonlinear programming model based on discrete method and analytical method was investigated, and several regression algorithms including Levenberg-Marquardt, Quasi-Newton, Gradient, Conjugate-Gradient, Newton, Principal-Axis and Nminimize algorithms were used to realize this model. A sample from Varian medical accelerator was used to test these two methods. The testing results showed that the root mean square of the reconstructed PDD could arrive at 0.15% in discrete method and 0.16% in analytical method, and the reconstructed photon energy spectra agreed well with the original by using Levenberg-Marquardt, Quasi-Newton and Conjugate Gradient algorithms in discrete method, and by using Levenberg-Marquardt, Quasi-Newton,Gradient and Principal-Axis algorithms in analytical method. The results showed that the above model in both discrete model and analytical model by several nonlinear regression algorithms could reconstruct photon energy spectra effectively, especially, both the Levenberg-Marquardt and Quasi-Newton algorithms enjoyed the great accuracy to photon energy spectrum reconstruction to solve both the discrete and analytical methods.
photon energy spectra medical accelearator radiotherapy nonlinear programming model
LI Gui ZHENG Hua-Qing WU Yi-Can
Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui, China, 230031 Engineering Te Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui, China, 230031 School of Nucl
国际会议
南京
英文
437-443
2009-10-23（万方平台首次上网日期，不代表论文的发表时间）