摘要
医学图像配准是医学图像分析诊断的基础,也是图像融合等图像处理需要先行解决的问题。首先用Canny算子提取图像的边缘,再用K-Means聚类算法进行聚类分析提取轮廓特征点,然后提出了一种改进的粒子群优化(IPSO)算法来求解配准所需的空间变换参数。实验结果表明:改进PSO能够迅速地在全局范围内找到最优解,应用于多模态医学图像配准是可行的。
Medical image registration is the first step for image fusion and other imaging process.In this paper,The image edges are first detected by using Canny operator,then the contour feature points are extracted by K-means algorithm,and translation parameters are calculated by using a Improved Particle Swarm Optimization （IPSO） algorithm.Experiments show that this approach is efficient and can avoid local minimum.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第32期237-240,共4页
Computer Engineering and Applications
关键词
医学图像配准
CANNY算子
K-MEANS聚类
IPSO
medical image registration
canny operator
K-means clustering algorithm
Improved Particle Swarm Optimization（IPSO）
