Pulmonary Nodule Candidates Segmentation Based on Circle Dependent C-V Level Set for CT Images
基于圆形约束C-V水平集的肺部CT图像病灶分割

Problems of segmentation of pulmonary nodule candidates from CT images were studied in paper,the image segmentation method proposed by Chan-Vese was analysed and improved.A new level set method based on circle dependent had been deduced,and then an algorithm for segmentation of pulmonary nodule candidates in CT images had been presented,it solved the problem of detecting multi-circle areas with different sizes in an image.Experiments had been done for segmentation of synthetic and clinical pulmonary images by the proposed algorithm,the experiment results show that it can detect multi-circles areas correctly and efficiently,and it is robust to resist noise disturbance.This algorithm has advantages for the realization of automatic detection for lung nodules in pulmonary CT images.