首页> 外文会议>Evolutionary Computation, 2005. The 2005 IEEE Congress on >Ant colony system for the beam angle optimization problem in radiotherapy planning: a preliminary study
【24h】

Ant colony system for the beam angle optimization problem in radiotherapy planning: a preliminary study

机译:放射治疗计划中射束角度优化问题的蚁群系统:初步研究

获取原文

摘要

Intensity-modulated radiotherapy (IMRT) is being increasingly used for treatment of malignant cancer. Beam angle optimization (BAO) is an important problem in IMRT. In this paper, an emerging population-based meta-heuristic algorithm named ant colony optimization (ACO) is introduced to solve the BAO problem. In the proposed algorithm, a multi-layered graph is designed to map the BAO problem to ACO, and a heuristic function based on the beam's-eye-view dosimetrics (BEVD) score is introduced. In order to verify the feasibility of the presented algorithm, a clinical prostate tumor case is employed, and the preliminary results demonstrate that ACO appears more effcient than genetic algorithm (GA) and can find the optimal beam angles within a clinically acceptable computation time.
机译:调强放射疗法(IMRT)正越来越多地用于治疗恶性肿瘤。束角优化(BAO)是IMRT中的重要问题。本文提出了一种新的基于人口的元启发式算法,称为蚁群优化(ACO),以解决BAO问题。在所提出的算法中,设计了一个多层图将BAO问题映射到ACO,并引入了基于光束的眼视剂量学(BEVD)得分的启发式函数。为了验证所提出算法的可行性,采用了临床前列腺肿瘤病例,初步结果表明,ACO比遗传算法(GA)更有效,并且可以在临床可接受的计算时间内找到最佳光束角。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号