Tracking of Carotid Arteries in Ultrasound Images

Shubao Liu, Dirk Padfield, and Paulo Mendonca

Abstract. We introduce an automated method for the 3D tracking of carotids acquired as a sequence of 2D ultrasound images. The method includes an image stabilization step that compensates for the cardiac and respiratory motion of the carotid, and tracks the carotid wall via a shape and appearance model trained from representative images. Envisaging an application in automatic detection of plaques, the algorithm was tested on ultrasound volumes from 4,000 patients and its accuracy was evaluated by measuring the distance between the location of more than 4,000 carotid plaques and the location of the carotid wall as estimated by the proposed algorithm. Results show that the centroids of over 95% of the carotid plaques in the dataset were located within 3 mm of the estimated carotid wall, indicating the accuracy of the tracking algorithm.

LNCS 8150, p. 526 ff.

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