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The analysis of the carotid wall is of paramount importance in clinical practice. In fact, the intima-media thickness is a risk index for some of the most severe acute cerebrovascular pathologies; hence, the need for an accurate segmentation of the different layers of the carotid artery. In the past ten years, a wide variety of algorithms for the carotid tunica segmentation have been proposed, but they require a certain degree of user interaction. In this paper we propose a novel approach to the completely user-independent segmentation of the carotid artery wall. Our algorithm has been designed for the extraction of the intima and media layers of the distal carotid wall, based on ultrasonic B-Mode images. We evaluated the performance of the algorithm on a set of 63 images and compared the automatic segmentation to that traced by a trained operator. We obtained a mean error lower than 1.3 pixel both on the intima and media layers, which is comparable to that obtained by means of operator dependent techniques.
Delsanto et al. (Sat,) studied this question.