DocumentCode :
2729515
Title :
Ant colony system for the beam angle optimization problem in radiotherapy planning: a preliminary study
Author :
Li, Yongjie ; Yao, Dezhong ; Chen, Wufan ; Zheng, Jiancheng ; Yao, Jonathan
Author_Institution :
Sch. of Lfe Sci. & Technol., UESTC, Chengdu, China
Volume :
2
fYear :
2005
fDate :
2-5 Sept. 2005
Firstpage :
1532
Abstract :
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.
Keywords :
cancer; dosimetry; genetic algorithms; medical computing; radiation therapy; tumours; ant colony system; beam angle optimization problem; beam-eye-view dosimetrics score; clinical prostate tumor; genetic algorithm; heuristic function; intensity-modulated radiotherapy; malignant cancer treatment; multilayered graph; optimal beam angle; population-based metaheuristic algorithm; radiotherapy planning; Algorithm design and analysis; Ant colony optimization; Cancer; Genetic algorithms; Intensity modulation; Medical treatment; Neoplasms; Optical modulation; Optimization methods; Technology planning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Print_ISBN :
0-7803-9363-5
Type :
conf
DOI :
10.1109/CEC.2005.1554871
Filename :
1554871
Link To Document :
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