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.
脑电(Electroencephalography,EEG)和功能磁共振(Functional magnetic resonance imaging,fMRI)技术的结合,可以实现两者优势的互补,获得更加合理的源定位结果。本文报道的是一种将fMRI先验信息结合到脑电源定位中的新方法。在该方法中,先利用SPM方法计算获得fMRI的统计映射参数,然后将基于计算获得的统计参数构造的权矩阵结合到FOCUSS的迭代过程中,对脑电的反演提供具有fMRI先验空间位置信息的约束,提高脑电的源空间定位精度,从而获得更加合理的定位结果。通过对一形状知觉实验fMRI和脑电数据的结合定位分析,结果初步证实了改进方法能获得和生理更加一致的结果。
