An Improved Target Extraction Algorithm Based on Region Growing for Lung CT Image
An efficient target extraction algorithm for lung CT image is proposed in this paper. First, it selects the gray average of ROI as the gray of seed points, and hits the seed points by erosion algorithm. At the same time it adopts the average value and variance of the region as the similarity criteria to improve the accuracy of the algorithm. Finally, the targets are extracted gradually by multilevel gray processing method avoiding the disturbed of the other parts in lung. The experiment results demonstrate that our algorithm is efficient in lung nodule extraction of ROI, and can offer more information for pathological analysis and diagnosis.
Li Ke Dan Yang Xu Wang
College of Information Science & Engineering, Northe astern University, Shenyang, Liaoning 110004, P College of Information Science & Engineering, Northe astern University, Shenyang, Liaoning 110004, P
国际会议
北京
英文
590-594
2007-05-23（万方平台首次上网日期，不代表论文的发表时间）