Automatic Initialization Algorithm for Carotid Artery Segmentation in CTA Images [chapter]

Martijn Sanderse, Henk A. Marquering, Emile A. Hendriks, Aad van der Lugt, Johan H. C. Reiber
2005 Lecture Notes in Computer Science  
Analysis of CT datasets is commonly time consuming because of the required manual interaction. We present a novel and fast automatic initialization algorithm to detect the carotid arteries providing a fully automated approach of the segmentation and centerline detection. First, the volume of interest (VOI) is estimated using a shoulder landmark. The carotid arteries are subsequently detected in axial slices of the VOI by applying a circular Hough transform. To select carotid arteries related
more » ... nals in the Hough space, a 3-D, direction dependent hierarchical clustering is used. To allow a successful detection for a wide range of vessel diameters, a feedback architecture was introduced. The algorithm was designed and optimized using a training set of 20 patients and subsequently evaluated using 31 test datasets. The detection algorithm, including VOI estimation, correctly detects 88% of the carotid arteries. Even though not all carotid arteries have been correctly detected, the results are very promising.
doi:10.1007/11566489_104 fatcat:gnkofygqwralxmx5reg52k5cta