Segmentation of ulcerated plaque: a semi-automatic method for tracking the progression of carotid atherosclerosis

Abstract

A semi-automatic method for segmentation of three-dimensional carotid vascular ultrasound (US) images is presented. The method is based on a dynamic balloon model represented by a triangulated mesh. The mesh is manually placed within the interior of the carotid arteries, then is driven outward until it reaches the vessel wall by applying an inflation force to the mesh. Once the mesh is in close proximity to the vessel wall, it is further deformed using an image-based force, in order to better localize the boundary. The authors examine the ability of the segmentation method to segment in vivo 3D US images of the carotid arteries. They furthermore examine its ability to distinguish subtle changes in vessel morphology, with the ultimate goal being to detect the progression or regression of atherosclerotic plaque. Two nearly identical common carotid vessel phantoms were imaged using a three-dimensional US imaging system, automatically registered, then segmented using the semi-automatic algorithm. The fabrication of the two phantoms was identical except for the inclusion of a hemispherical ulceration cut into one of the vessels. The two segmented surfaces were compared by determining the distance between them at each point along one of the two surfaces. Since the 3D US images had been previously registered, the two segmented surfaces are expected to overlap everywhere except near the region of ulceration. This was confirmed to within a 0.3 mm error.