This paper proposes an integrative approach that facilitates physicians to semi automatically obtain a 3-D symbolic representation of cerebral vasculature from 3-D magnetic resonance angiography (MRA) datasets. In this approach, firstly vessels are segmented by morphology method followed by 3-D parallel thinning to obtain the one voxel wide skeleton. Then a novel method employing general tree and its combinations is introduced to depict the 3-D geometrical structure of the vasculature. With the generated tree, post processing, such as traversal and visualization, is implemented. The method has been tested on both synthetic images and real images; the results are promising. A system based on this approach provides a useful visualization tool of the intracerebral vasculature for clinic applications.