摘要
为解决肺气肿的定量分析与辅助诊断问题,根据肺部高分辨率CT图像的特点,应用自动阈值分割与轮廓跟踪方法提取肺部实质区域,并应用基于密度分布的肺气肿量化诊断标准确定病变区域与程度.实验证明,该方法能准确、有效地对肺部区域实行全自动分割,并对病变区域进行统计分析,最终实现肺气肿的量化分析与准确诊断.
Abstract： In order to implement the quantitative analysis and aided diagnosis of emphysema, an aaaputive thresholdsegmenting and contour-tracing method was proposed to automatically extract the information of pulmonary parenchyma from high-resolution CT images, and the region and severity of emphysema were then determined according to the quantitative analysis criterion based on density distribution. Experimental results show that the proposed method can segment the pulmonary parenchyma automatically with accurate and effective results, and can statistically analyze the pathological change regions, thus implementing the quantitative analysis and exact diagnosis of emphysema.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2008年第1期72-75,共4页
Journal of South China University of Technology(Natural Science Edition)
关键词
高分辨率CT
医学图像
肺部区域
分割
辅助诊断
high resolution CT
medical image
lung region
segmentation
aided diagnosis
