中国组织工程研究与临床康复2008，Vol.12Issue(22)：4380-4384,5.
基于SAPSO优化三维Otsu方法的医学图像分割算法
Three-dimensional Otsu's method for medical image segmentation based on a simulated annealing particle swarm optimization algorithm
摘要
Abstract
Medical image has rich content, various features, and multiple dimensions. Therefore, it is more difficult to segment medical image compared with general image. Aiming at this, a three-dimensional Otsu's method based on an improved particle swarm optimization (PSO) algorithm has been purposed for medical image segmentation. Three-dimensional Otsu's method requires much computation. PSO algorithm can be used to search threshold vectors. Each particle represents a feasible threshold vector. Thus, the optimal threshold can be acquired by the cooperation of particle swarm. Because the PSO algorithm easily sinks into local optimization, so a simulated annealing particle swarm optimization (SAPSO) algorithm has been purposed. The three-dimensional Otsu's method based on SAPSO can rapidly and exactly get the entire optimal results. Simulation experiment results demonstrated that this method could acquire ideal results with less computation.关键词
粒子群算法/OTSU方法/模拟退火粒子群算法/图像分割/数字医学分类
医药卫生引用本文复制引用
白杨..基于SAPSO优化三维Otsu方法的医学图像分割算法[J].中国组织工程研究与临床康复,2008,12(22):4380-4384,5.基金项目
浙江省自然科学基金资助项目(Y104592) （Y104592）
浙江省教育厅科研项目(20041032) the Natural Science Foundation of Zhejiang Province, No. Y104592 （20041032）
The Scientific Research Program of Department of Education of Zhejiang Province, No. 20041032 （）
