Pulmonary nodules are potential manifestation of lung cancer. Accurate segmentation of juxta-vascular nodules and ground glass opacity (GGO) nodules is an important and active area of research in medical image processing. At present, the classical active contour models (ACM) for segmentation of pulmonary nodules may cause the problem of boundary leakage. In order to solve the problem, a new fuzzy speed function-based active model for segmentation of pulmonary nodules is proposed in this paper. The fuzzy speed function incorporated into the ACM is calculated by the degree of membership based on intensity feature and local shape index. At the boundary of pulmonary nodules, the fuzzy speed function approaches zero and the evolution of the contour curve will stop, so the accurate segmentation of pulmonary nodules can be obtained. Experimental results on juxta-vascular nodules and GGO nodules show that the proposed ACM can achieve accurate segmentation.
Keywords: Image segmentation; active contour models (ACM); boundary leakage; fuzzy clustering; fuzzy speed function.