A Dynamic Adaptive 3D Voxel-growing Segmentation Algorithm for Pulmonary CT Images
基于动态自适应体素生长的肺部 CT图像3维分割算法

A novel algorithm based on dynamic adaptive voxel-growing method is proposed to segment 3D CT pulmonary volumes.It selects the optimal parameters for segmentation by dynamically adjusting statistical information about previous segmented regions.To avoid the disadvantage of leaking during segmentation with the conventional voxel-growing based methods,it adopts a process to mutually utilize segment results between both of lateral lung leaves,which in turn benefit the discriminative segmentation on left and right lung leaves.Compared with conventional algorithms,the accuracy and robustness of segmentation are enhanced,and still this algorithm has the advantage of pure 3D processing ability.Groups of experimental data is verified with this algorithm,including data about the healthy people and types of patients with lung diseases.Results are effective,which imply that this algorithm is potentially valid for future clinical diagnosis applications.