The main contribution of this article is a new method of segmentation of carotid artery based on original authors inner path finding algorithm and active contours without edges segmentation method for vessels wall detection. Instead of defining new force to being minimized or intensity metric we decide to find optimal weight of image – dependent forces. This allows our method to be easily reproduced and applied in other software solutions. We judge the quality of segmentation by dice coefficient between manual segmentation done by a specialist and automatic segmentation performed by our algorithm. We did not find any other publication in which such approach for carotid artery bifurcation region segmentation has been proposed or investigated. The proposed algorithm has shown to be reliable method for that task. The dice coefficient at the level of 0.949(0.050 situates our algorithm among best state of the art methods for those solutions. That type of segmentation is the main step performed before sophisticated semantic analysis of complex image patterns utilized by cognitive image and scene understanding methods. The complete diagnostic record (Electronic Health Record – EHR) obtained that way consists private biometric data and its safety is essential for personal and homeland security.