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An automated method for the segmentation and tracking of moving vessel walls in 2D ultrasound image sequences is introduced. The method was tested on simulated and real ultrasound image sequences of the carotid artery. Tracking was achieved via a self organizing neural network known as Growing Neural Gas. This topology-preserving algorithm assigns a net of nodes connected by edges that distributes itself within the vessel walls and adapts to changes in topology with time. The movement of thedoi:10.1109/icpr.2010.623 dblp:conf/icpr/AzarM10 fatcat:kydvxvuutrfsle2oomsf27f3y4