论文标题
分布式目标功能评估，以优化放射治疗治疗计划
Distributed Objective Function Evaluation for Optimization of Radiation Therapy Treatment Plans
论文作者
论文摘要
放射治疗治疗计划的现代工作流程涉及数学优化，以确定每个患者病例的最佳治疗机参数。优化问题在计算上可能很昂贵，需要迭代优化算法要解决。在这项工作中，我们研究了一种分布计算跨计算节点的辐射疗法优化问题的目标函数计算的方法。我们在TROTS数据集上测试了我们的方法（包括实际临床患者病例中的优化问题），其中使用IPOPT优化求解器在领导者/追随者类型方法中进行并行化。我们表明，我们的方法可以有效地利用多个计算节点，与串行版本相比，加速度约为2-3.5倍。
The modern workflow for radiation therapy treatment planning involves mathematical optimization to determine optimal treatment machine parameters for each patient case. The optimization problems can be computationally expensive, requiring iterative optimization algorithms to solve. In this work, we investigate a method for distributing the calculation of objective functions and gradients for radiation therapy optimization problems across computational nodes. We test our approach on the TROTS dataset -- which consists of optimization problems from real clinical patient cases -- using the IPOPT optimization solver in a leader/follower type approach for parallelization. We show that our approach can utilize multiple computational nodes efficiently, with a speedup of approximately 2-3.5 times compared to the serial version.
