基于遗传算法的胸部CT图像肺组织分割  

Segmentation of Lung Parenchyma in Chest CT Images Based on Genetic Algorithm

作　　者：秦晓红[1] 孙丰荣[1] 王长宇[1] 李艳玲[1] 王晓婧[1] 陈力华[1] 

机构地区：[1]山东大学信息科学与工程学院,济南250100

出　　处：《计算机工程》2007年第19期188-189,192,共3页Computer Engineering

基　　金：国家自然科学基金资助项目(60571040);山东省优秀中青年科学家科研奖励基金资助项目(2005BS01006)

摘　　要：肺组织分割是肺结节检测、肺功能定量分析、三维重建与可视化计算等胸部CT图像分析处理的基础。该文采用了一种基于遗传算法的边缘检测方法直接分割原始胸部CT图像的肺组织,利用遗传算法的全局寻优能力,以最大类间方差为适应度函数自动搜索最佳边缘检测阈值,并结合形态学处理提取肺组织边缘以实现肺组织分割。实验结果表明,该方法能简化分割处理,且分割效果较好,有不错的应用前景。　The segmentation of lung parenchyma is the foundation of chest CT image processing,such as lung nodule detection,quantitative analysis of lung function,three-dimensional reconstruction,and visualization analysis.This paper uses an edge detection method based on genetic algorithm to segment the lung parenchyma of original chest CT image.With global searching capacity and the largest variance between clusters as the fitness function,this method can search the optimal threshold of edge detection automatically,and extract the edge of lung parenchyma by combining morphologic processing to realize the segmentation of lung parenchyma.Experiment shows that the method can not only simplify the segmentation of lung parenchyma,but also achieve a good segmentation effect.It has a good foreground in application.

关 键 词：遗传算法 边缘检测 最大类间方差 肺组织分割 

分 类 号：TN911.73[电子电信—通信与信息系统]