放射治疗计划的神经网络优化算法

OPTIMIZATION ALGORITHM OF RADIOTHERAPY TREATMENT PLANNING USING LINEAR PROGRAMMING BASED ON NEURAL NETWORK(LPNN)

本文针对常用的治疗计划线性规划法 ,首次提出了一种基于神经网络的优化算法。与传统方法相比 ,神经网络优化算法可以克服传统算法求解时出现的问题 ,具有很强的鲁棒性和非线性动态系统的特征 ,可以减小问题的规模 (待求的自由变量个数 )。

A neural network model for linear programming was proposed to optimize radiotherapy treatment planning. Comparing with traditional methods, neural networks exhibit notable robustness since their functions are not affected by parameter variations over a wide range. Linear programming based on neural networks (LPNN) can speed convergence, decrease scope of problems, and cut down extra slack variables and surplus variables. An example of the use of LPNN in three-dimensional stereotactic radiotherapy treatment planning was also described.