Accelerating the Radiotherapy Planning with a Hybrid Method of Genetic Algorithm and Ant Colony System

  • Yongjie Li
  • Dezhong Yao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4222)


Computer-aided radiotherapy planning within a clinically acceptable time has the potential to improve the therapeutic ratio by providing the optimized and customized treatment plans for the tumor patients. In this paper, a hybrid method is proposed to accelerate the beam angle optimization (BAO) in the intensity modulated radiotherapy (IMRT) planning. In this hybrid method, the genetic algorithm (GA) is used to find the rough distribution of the solution, i.e., to give the initial pheromone distribution for the following ant colony system (ACS) optimization. Then, the ACS optimization is implemented to find the precise solution of the BAO problem. The comparisons of the optimization on a clinical nasopharynx case with GA, ACS and the hybrid method show that the proposed algorithm can obviously improve the computation efficiency.


Genetic Algorithm Dose Distribution Travel Salesman Problem Radiotherapy Planning Quadratic Assignment Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yongjie Li
    • 1
  • Dezhong Yao
    • 1
  1. 1.School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina

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