Quantitative information about the geometry of the carotid artery bifurcation may help in predicting the development of atherosclerosis. A geodesic active contours based segmentation method combining both gradient and intensity information was developed for semi-automatic, accurate and robust quantification of the carotid bifurcation angle in Black Blood MRA data. The segmentation method was evaluated by comparing its accuracy to inter and intra observer variability on a large dataset that has been acquired as part of a longitudinal population study which investigates the natural progression of carotid atherosclerosis. Furthermore, the method is shown to be robust to initialization differences. The bifurcation angle obtained from the segmented lumen corresponds well with the angle derived from the manual lumen segmentation, which demonstrates that the method has large potential to replace manual segmentations for extracting the carotid bifurcation angle from Black Blood MRA data.
Hui Tang Lucas J.van Vliet Wiro J.Niessen Robbert S.van Onkelen Theo van Walsum Reinhard Hameeteman Michiel Schaap Fufa.L.Tori Quirijn J.A.van den Bouwhuijsen Jacqueline C.M.Witteman Aad van der Lugt
Departments of Radiology and Medical Informatics Department of Image Science and TechnologyFaculty o Department of Image Science and TechnologyFaculty of Applied Science, Delft University of Technology Departments of Radiology and Medical Informatics Department of Image Science and Technology Faculty Departments of Radiology and Medical Informatics Department of EpidemiologyErasmus MC- University Me Departments of Radiology and Medical Informatics Department of EpidemiologyErasmus MC- University Medical Center Rotterdam, The Netherlands