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.