A three-dimensional representation of vasculature system can be extremely important in image-guided neurosurgery

pre-surgical planning. In this paper

a multi-attribute based spatial continuity fuzzy clustering algorithm (multi-attribute based spatial continuity fuzzy clustering algorithm

MASCFCM) is proposed for segmenting entire blood vessels from the time of flight magnetic resonance angiography (TOF MRA) images. This clustering method takes both the intensity information and the geometrical information into account

while most of the current clustering methods only deal with the former. In this method

a new dissimilarity method

which integrates the intensity and the geometry shape dissimilarity

is introduced. Because of the presence of the geometrical information

the new measure is able to differentiate the pixels with similar intensity values within different geometrical shape structures. To evaluate the algorism

the algorithm is exerted on both 2D and 3D images and the experimental results show that the new algorithm can achieve better segmentation results.