A semi-automatic method for segmentation of the carotid bifurcation and bifurcation angle quantification on black blood MRA

Authors:
Hui Tang;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;Lucas J. van Vliet;Wiro J. Niessen
Affiliations:
Departments of Radiology and Medical Informatics, Erasmus MC, University Medical Center Rotterdam, The Netherlands and Department of Image Science and Technology, Faculty of Applied Science, Delft ...;Departments of Radiology and Medical Informatics, Erasmus MC, University Medical Center Rotterdam, The Netherlands and Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, ...;Departments of Radiology and Medical Informatics, Erasmus MC, University Medical Center Rotterdam, The Netherlands;Departments of Radiology and Medical Informatics, Erasmus MC, University Medical Center Rotterdam, The Netherlands;Departments of Radiology and Medical Informatics, Erasmus MC, University Medical Center Rotterdam, The Netherlands;Departments of Radiology and Medical Informatics;Departments of Radiology and Medical Informatics, Erasmus MC, University Medical Center Rotterdam, The Netherlands and Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, ...;Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, The Netherlands;Departments of Radiology and Medical Informatics, Erasmus MC, University Medical Center Rotterdam, The Netherlands;Department of Image Science and Technology, Faculty of Applied Science, Delft University of Technology, The Netherlands;Departments of Radiology and Medical Informatics, Erasmus MC, University Medical Center Rotterdam, The Netherlands and Department of Image Science and Technology, Faculty of Applied Science, Delft ...
Venue:
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
Year:
2010

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Abstract

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.