Automated lumen segmentation and estimation of numerical attributes of common carotid artery using longitudinal B-mode ultrasound images

Aortic elasticity and stiffness has been proven to be a strong independent predictor of cardio vascular diseases (CVD). Many features have been used to quantify arterial elasticity and stiffness. This paper describes a novel and automated technique for segmentation and boundary detection of lumen of common carotid artery (CCA) using longitudinal B-mode ultrasound images. Numerical attributes are measured from the detected boundary of lumen. The main objective of this work is to determine good arterial features based on the attributes to characterize the elasticity and stiffness of CCA. Attributes are measured for each frame and analyzed for minimum two cardiac cycles to see the changes from systole to diastole. Findings of this analysis would be very useful for the diagnosis of abnormalities in the CCA.