Atherosclerosis disease is one of the most important causes of death in the world. Carotid artery stenosis causes narrowing of blood vessels and this forward results with stroke. The carotid arteries enter from the skull cavity and show close proximity to the bone and osteoid structures. Bone tissue and contrast enhanced carotid arteries generally cannot distinguish when vessel evaluation is performed. In this study, the segmentation of carotid arteries and extraction of bone regions are done with seeded region-growing and random walk segmentation methods. And, methods are compared. These methods are applied on different patients' CTA images and the performance evaluations are done with statistical, area and distance based metrics. Region growing and random walk methods in vessel segmentation give approximately similar results. In general, random walk is more successful according to average results in vessel segmentation. It is observed that region growing gives more successful results in bone segmentation and execution time is shorter than random walk method.