基于空间模糊C均值和图割的肝脏CT序列图像分割  

Liver Segmentation from CT Volumes Based on Spatial Fuzzy C-Means and Graph Cuts

作　　者：杨勍[1] 赵于前[1,2] 张帆 廖苗[1] Yang Qing;Zhao Yuqian;Zhang Fan;Liao Miao(School of Automation,Central South University,Changsha 410083,Hunan,China;Hunan Engineering and Technology Research Center of High Strength Fastener Intelligent Manufacturing,Changde 415701,Hunan,China)

机构地区：[1]中南大学自动化学院,湖南长沙410083 [2]湖南省高强度紧固件智能制造工程技术研究中心,湖南常德415701

出　　处：《激光与光电子学进展》2022年第12期420-429,共10页Laser & Optoelectronics Progress

基　　金：国家自然科学基金(61772555,62076256)。

摘　　要：肝脏分割是计算机辅助肝脏疾病诊断、治疗和手术的重要步骤,提出一种基于空间模糊C均值和图割的CT图像肝脏分割方法。首先,为去除毗邻器官和组织对肝脏分割的影响,采用阈值、投影和三维区域生长法从原始CT图像中去除脊柱、肋骨,接着采用K-means聚类和二值形态学重建方法去除右肾。然后,采用空间模糊C均值从初始切片中分割肝脏,再结合CT切片的空间、形状和灰度特性运用图割算法迭代分割剩余切片。最后,根据形态学操作和解剖学知识去除肝脏分割结果中的下腔静脉区域。实验结果证明,与其他同类方法相比该方法可获得更好的分割效果。Liver segmentation is an important step in computer-aided diagnosis, treatment and surgery of liver diseases. A liver segmentation method based on spatial fuzzy C-means and graph cuts is proposed. Firstly, in order to remove the influence of adjacent organs and tissues on liver segmentation, the spine and ribs are removed from original CT images by thresholding,projection method and 3D region growing, and the right kidney is removed by K-means and binary morphological reconstruction method. Then, liver is segmented by spatial fuzzy C-means from the initial liver slice. The remaining slices are segmented iteratively by graph cuts based on the spatial, shape and gray scale characteristics of CT volumes. Finally, the inferior vena cava is removed by morphological operations and anatomical knowledge. The experimental results show that the proposed method can obtain better segmentation performance than those of other similar methods.

关 键 词：医用光学与生物技术 图割 肝脏分割 空间模糊C均值 先验知识 

分 类 号：O436[机械工程—光学工程]