基于CT图像的自动肺实质分割方法

在肺癌、肺气肿等肺部疾病计算机辅助诊断方法中,肺实质分割是最核心的步骤.提出一种基于三维CT图像序列的新的自动肺实质分割方法,综合利用了阈值分割、区域增长及数学形态学等算法,并在特定体层通过图搜索算法精确定位左右肺前后连接线狭窄区域,有效解决了肺实质边缘结节易分割遗漏及左右肺分离的难题.通过多组胸部CT序列图像的实验证明,该方法对于肺实质分割非常精确有效.

Automatic Lung Parenchyma Segmentation on CT Image

The automatic segmentation of lung parenchyma is one of the key techniques to the computer-aided diagnosis(CAD) system for lung cancer,emphysema and other lung diseases.A new automatic lung segmentation based on the 3-D CT image series is proposed integrating the adaptive gray-level threshold,region growing and math morphological algorithms together.And the graph search algorithm is used at specified layers to position accurately the narrow zone formed by the anterior and posterior lines connecting the left and right lung,thus overcoming efficiently the difficulties that the nodules at lung edge are easy to be missed and how to separate the left lung from right one.The experimental results of many sets of CT images verified that the technique proposed is highly exact and efficient for lung parenchyma segmentation.