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A Preliminary Study of Automatic Delineation of Eyes on CT Images Using Ant Colony Optimization 被引量:2

A Preliminary Study of Automatic Delineation of Eyes on CT Images Using Ant Colony Optimization
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摘要 Eyes are important organs-at-risk (OARs) that should be protected during the radiation treatment of those head tumors. Correct delineation of the eyes on CT images is one of important issues for treatment planning to protect the eyes as much as possible. In this paper, we propose a new method, named ant colony optimization (ACO), to delineate the eyes automatically. In the proposed algorithm, each ant tries to find a closed path, and some pheromone is deposited on the visited path when the ant fmds a path. After all ants fmish a circle, the best ant will lay some pheromone to enforce the best path. The proposed algorithm is verified on several CT images, and the preliminary results demonstrate the feasibility of ACO for the delineation problem. Eyes are important organs-at-risk (OARs) that should be protected during the radiation treatment of those head tumors. Correct delineation of the eyes on CT images is one of important issues for treatment planning to protect the eyes as much as possible. In this paper, we propose a new method, named ant colony optimization (ACO), to delineate the eyes automatically. In the proposed algorithm, each ant tries to find a closed path, and some pheromone is deposited on the visited path when the ant fmds a path. After all ants fmish a circle, the best ant will lay some pheromone to enforce the best path. The proposed algorithm is verified on several CT images, and the preliminary results demonstrate the feasibility of ACO for the delineation problem.
出处 《Journal of Electronic Science and Technology of China》 2007年第1期66-69,共4页 中国电子科技(英文版)
基金 Supported by the 973 Project of China (No. 2003CB716106) the National Natural Science Foundation of China (No. 30500140 and 90208003)
关键词 automatic delineation CT images ant colony optimization automatic delineation CT images ant colony optimization
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  • 1杨清夙,游志胜,张先玉.基于豪斯多夫距离的快速多人脸检测算法[J].电子科技大学学报,2004,33(4):407-409. 被引量:9
  • 2段海滨,王道波,朱家强,黄向华.蚁群算法理论及应用研究的进展[J].控制与决策,2004,19(12):1321-1326. 被引量:211
  • 3宋加涛,刘济林,池哲儒,王蔚.人脸正面图像中眼睛的精确定位[J].计算机辅助设计与图形学学报,2005,17(3):540-545. 被引量:13
  • 4罗明刚,李一民,曾素娣.基于Adaboost算法的人脸检测研究[J].计算机与数字工程,2007,35(2):7-8. 被引量:10
  • 5RIOPKA T P, BOULT T. The eyes have it[C]//Proceeding of the 2003 ACM SIGMM Workshop on Biometrics Methods and Applications. California: ACM Press, 2003: 9-16.
  • 6VIOLA P J M. Robust real-time object detection[R]. Technical Report 2001/01, Compaq CRL, 2001.
  • 7RAINER L, JOCHEN M. An extended set of haar-like features for rapid object detection[J]. IEEE ICIP, 2002, 900-903.
  • 8FREUND Y, SCHAPIRE R E. A decision-theoretic generalization of on-line learning and an application to booosting[J]. Journal of Computer and System Sciences, 1997, 55(1): 11-139.
  • 9LIENHART R, KURANOV A, PISAREVSKY V. Empirical analysis of detection cascades of boosted classifiers for rapid object deteetion[C]//Proceedings of the 25th German Pattern Recognition Symposium, Magdeburg ICIP, 2003: 297-304.
  • 10ARIZA A E, SANDOVAL C F. Strategies for updating link states in QoS routers[J]. Electronics Letters, 2000, 36(20): 1749-1750.

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