基于改进蚁群算法的CT图像边缘检测方法研究  

Research of CT image edge detection based on improved ant colony algorithm

作　　者：张景虎[1] 郭敏[1] 王亚文[2] 

机构地区：[1]陕西师范大学计算机科学学院 [2]西安工业大学计算机科学与工程学院,西安710032

出　　处：《计算机应用》2008年第5期1236-1239,共4页journal of Computer Applications

基　　金：陕西省自然科学基金资助项目(2005A12)

摘　　要：将蚁群算法(ACA)应用于CT图像边缘检测领域,提出一种新的CT图像边缘检测方法。为了提高检测效率、精确度和对各类CT图像的适应性,对蚁群算法进行了改进,并针对图像中的不同内容采取不同的转移策略和信息素更新规则。实验结果表明了该算法的有效性,满足了CT图像三维重建的需求。Ant Colony Algorithm（ACA） was applied in CT image edge detection and a new method of CT image edge detection based on ant colony algorithm was proposed. In order to improve the efficiency of algorithm, detection accuracy and adaptability to various CT images, the basic ant colony algorithm was modified by applying different transfer principles and pheromone updating rules in accordance with different contents of CT image. The computer experiments demonstrate the effectiveness of the proposed algorithm, which satisfies the demand of 3D reconstruction of CT. image.

关 键 词：蚁群算法 边缘检测 CT图像 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]