The complete segmentation of the common carotid artery (CCA) bifurcation in ultrasound images is important for the evaluation of atherosclerosis disease and the quantification of the risk of stroke. This requires the extraction of the intima-media complex (IMC), the delineation of the lumen the atherosclerotic carotid plaque and measurement of the artery stenosis. The current research proposes an automated segmentation system for the complete segmentation of the CCA bifurcation in ultrasound images, which is based on snakes. The algorithm was evaluated on 20 longitudinal ultrasound images of the CCA bifurcation with manual segmentations available from a neurovascular expert. The manual mean±SD measurements were for the IMT: (0.96±0.22) mm, lumen diameter: (5.59±0.84) mm and ICA origin stenosis (48.1±11.52) %, while the automated measurements were for the IMT: (0.93±0.22) mm, lumen diameter: (5.77±0.99) mm and ICA stenosis (51.05±14.51) % respectively. We found no significant differences between all manual and the automated segmentation measurements.