结合显著性和Graph cuts的肺区域图像分割

Lung Segmentation by Saliency and Graph Cuts

针对肺部CT图像灰度分布不均匀、各组织结构复杂导致难以准确地分割提取出肺区域的问题,提出了一种结合图像显著性和Graph cuts的肺区域自动分割方法.对10位病例的CT图像序列进行测试,结果表明:该方法可以自动完成肺区域分割,具有较高精度,且耗时较少.

The gray distribution in lung CT images is uneven and the structure is complex,which makes it difficult to accurately segment and extract the lung.Aiming at the problem,an automatic segmentation algorithm combined saliency with Graph cuts was proposed.The results of experiment on clinical chest CT images of 10 patients show that the segmentation of the lung can be completed automatically through the method,and it is accurate and costs less time.