This paper presents an effective approach to extract cerebrovascular tree from time-of-flight (TOF) magnetic resonance angiography (MRA) images. The approach consists of two segmentation stages. In the first stage, Gaussian filtering is implemented for the 3D volumetric field. By virtue of the maximum intensity projection (MIP) image segmented by the two dimensional OTSU algorithm, 3D vessel seeds are obtained. The region growing rule is defined by combining the global information with the local information, and then the rough segmentation is implemented by the region growing algorithm. In second stage, the original volume data is filtered by an anisotropic filtering based on Catt diffusion. A local adaptive C-V model is proposed, and the initial contour of the model is set by employing the first segmented vessels. Then the accurate segmentation is realized by the contour evolution. Experimental results show that the proposed algorithm is not only able to effectively segment the thick vessel, but also able to accurately extract the thinner vessels with weak boundaries.