Title :
Segmentation of the Outer Vessel Wall of the Common Carotid Artery in CTA
Author :
Vukadinovic, Danijela ; van Walsum, Theo ; Manniesing, Rashindra ; Rozie, Sietske ; Hameeteman, Reinhard ; De Weert, Thomas T. ; Van der Lugt, Aad ; Niessen, Wiro J.
Author_Institution :
Depts. of Radiol. & Med ical Inf., Erasmus MC, Rotterdam, Netherlands
Abstract :
A novel method is presented for carotid artery vessel wall segmentation in computed tomography angiography (CTA) data. First the carotid lumen is semi-automatically segmented using a level set approach initialized with three seed points. Subsequently, calcium regions located within the vessel wall are automatically detected and classified using multiple features in a GentleBoost framework. Calcium regions segmentation is used to improve localization of the outer vessel wall because it is an easier task than direct outer vessel wall segmentation. In a third step, pixels outside the lumen area are classified as vessel wall or background, using the same GentleBoost framework with a different set of image features. Finally, a 2-D ellipse shape deformable model is fitted to a cost image derived from both the calcium and vessel wall classifications. The method has been validated on a dataset of 60 CTA images. The experimental results show that the accuracy of the method is comparable to the interobserver variability.
Keywords :
angiocardiography; computerised tomography; image segmentation; medical image processing; 2D ellipse shape deformable model; GentleBoost framework; carotid lumen; common carotid artery; computed tomography angiography; outer vessel wall segmentation; Angiography; Calcium; Carotid arteries; Computed tomography; Costs; Deformable models; Image segmentation; Level set; Pixel; Shape; Carotid; classification; computed tomography angiography (CTA); outer vessel wall; segmentation; Algorithms; Angiography; Bayes Theorem; Carotid Artery, Common; Humans; Image Processing, Computer-Assisted; Normal Distribution; Tomography, X-Ray Computed;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2009.2025702