基于图论的肝肿瘤CT图像自动分割方法  

Graph-based Method for Liver Tumor CT Image Auto-segmentation

作　　者：艾海明[1] 吴水才[1] 高宏建[1] 赵磊[1] 曾毅[1] 

机构地区：[1]北京工业大学生物医学工程中心,北京100124

出　　处：《北京工业大学学报》2010年第4期572-576,共5页Journal of Beijing University of Technology

基　　金：北京市自然科学基金资助项目(3072004)

摘　　要：提出了一种肝肿瘤CT图像自动分割的方法,运用图中最小生成树寻找图像的同质区域,使用按级合并和路径压缩2种试探法,使得分割时程近似线性时间O(nlogn).对52幅肝肿瘤CT图像进行分割,结果表明,该方法分割实际图像的平均最小距离为8.7540,面积交迭度为95.15%,分割精确度优于同类自动分割算法.应用该方法能快速、准确地自动分割出肝肿瘤.A novel method for liver tumor CT image auto-segmentation is proposed in this paper.By utilizing minimal spanning tree of graph,the method can search for homogeneous region of image,and image segmentation can be conducted in time with union by rank and path compression.The method is evaluated via 52 liver tumor CT images,the results demonstrate that average minimum euclidean distance（AMED） and area overlap measure are 8.7540 and 95.15% respectively,and segmentation accuracy is optimal.These results show that the proposed method can auto-segment liver tumor quickly and precisely.

关 键 词：图论 CT图像 图像自动分割 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]