Automated detection of the carotid artery wall in longitudinal B-mode images using active contours initialized by the Hough transform

In this paper, a fully automatic active-contour-based segmentation method is presented, for detecting the carotid artery wall in longitudinal B-mode ultrasound images. A Hough-transform-based methodology is used for the definition of the initial snake, followed by a gradient vector flow (GVF) snake deformation for the final contour detection. The GVF snake is based on the calculation of the image edge map and the calculation of GVF field which guides its deformation for the estimation of the real arterial wall boundaries. In twenty cases there was no significant difference between the automated segmentation and the manual diameter measurements. The sensitivity, specificity and accuracy were 0.97, 0.99 and 0.98, respectively, for both diastolic and systolic cases. In conclusion, the proposed methodology provides an accurate and reliable way to segment ultrasound images of the carotid artery.