基于统计跳变回归分析的肺部CT图像分割  

Segmentation of CT image of lung based on statistical jump regression analysis

作　　者：张亮[1] 张建州[1] 

机构地区：[1]四川大学计算机学院,成都610065

出　　处：《计算机工程与应用》2008年第12期196-198,共3页Computer Engineering and Applications

摘　　要：在肺癌的放射治疗应用中,对肿瘤的分割是自动定位的关键。由于肺区CT图像中存在细小的支气管、血管以及纹理,这给肿瘤的分割带来了困难。用传统的滤波方法不能在抑制肺区内细节的同时保持肺区及肿瘤的边界。采用统计跳变回归分析方法对CT图像进行预处理,处理后的肺区中细小的支气管和血管以及纹理被抑制,并且该方法具有良好的保边性,这有利于之后对肺区和肿瘤的分割。实验表明该方法是有效的。The segmentation of tumor is an important step for automatic locating of tumor in the applications of radiotherapy for lung cancer.With the existence of small bronchus,vessels and textures in lung area,it is a challenge to segment tumor from the background.Conventional methods of filtering cannot restrain the details within the lung area without blurring the boundary of lung and tumor.Using a method based on statistical jump regression analysis which is mentioned in this paper as a preprocessing on CT image,small bronchus,vessels and textures can be restrained.Additionally,the method has an ideal feature of edge preservation,which is advantageous for further segmentation of lung and tumor.Experiment results show that this method is effective.

关 键 词：肺 肿瘤 CT图像 分割 统计跳变回归分析 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]