Abstract: A new automatic segmentation method of suspected lung nodules of edge-preserving smoothing and improved FCM algorithm is proposed.Firstly，the pulmonary parenchyma with smooth edge is separated from the original CT scans and the suspected lesions in the lung area are used by nonlinear anisotropic diffusion filtering for enhancement.Secondly，an improved Fuzzy C-Means（FCM） clustering algorithm is applied to the segmentation of the suspected lung nodules in different sizes.Experiment results indicate that the presented segmentation method of suspected lung nodules can be completed correctly and automatically，which achieves better performance than the conventional FCM algorithm and is much robust and efficient.

摘要： 提出一种基于保边滤波和改进FCM算法的疑似肺结节自动分割方法。首先，分离出边缘光滑的肺实质并通过非线性各向异性扩散滤波增强肺区疑似病灶，然后运用改进的模糊C-均值聚类算法分割出不同大小的疑似肺结节。实验结果证明，该方法能够自动、准确地完成疑似肺结节分割，比用传统的FCM算法取得更佳效果，并具有良好的鲁棒性和效率。