Characterization of a Completely User - Independent Algorithm for the Segmentation of Carotid Artery Ultrasound Images

The analysis of the carotid artery wall is crucial for the diagnosis of serious cardiovascular pathologies or for the assessment of a subject's cardiovascular risk. Several algorithms have been proposed for the segmentation of ultrasound carotid artery images, but almost all require a certain degree of user interaction. We recently developed a completely user-independent algorithm for the segmentation of the common carotid artery wall; specifically, the algorithm traces the contour of the interfaces between the lumen and the intima layer and between the media and adventitia layers. In this paper we show the characterization of the algorithm in terms of segmentation error. Moreover, we compared the output of the algorithm with the segmentations manually traced by experts. We show that our algorithm 's segmentation is not statistically from that of a trained operator and that the segmentation error is lower than 1 pixel for the lumen-intima interface and 1.5 pixels for the media-adventitia interface.