Carotid artery wall segmentation by coupled surface graph cuts

  • Authors:

  • Andres Arias;Jens Petersen;Arna van Engelen;Hui Tang;Mariana Selwaness;Jacqueline C. M. Witteman;Aad van der Lugt;Wiro Niessen;Marleen de Bruijne

  • Affiliations:

  • Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus MC, Rotterdam, The Netherlands;Image Group, Department of Computer Science, University of Copenhagen, Denmark;Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus MC, Rotterdam, The Netherlands;Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus MC, Rotterdam, The Netherlands, Faculty of Applied Sciences, Department of Imaging Science and Technol ...;Department of Radiology, Erasmus MC, Rotterdam, The Netherlands, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands, Department of Biomedical Engineering, Erasmus MC, Rotterdam, Th ...;Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands;Department of Radiology, Erasmus MC, Rotterdam, The Netherlands;Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus MC, Rotterdam, The Netherlands, Faculty of Applied Sciences, Department of Imaging Science and Technol ...;Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus MC, Rotterdam, The Netherlands, Image Group, Department of Computer Science, University of Copenhagen, ...

  • Venue:
  • MCV'12 Proceedings of the Second international conference on Medical Computer Vision: recognition techniques and applications in medical imaging
  • Year:
  • 2012

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Abstract

We present a three-dimensional coupled surface graph cut algorithm for carotid wall segmentation from Magnetic Resonance Imaging (MRI). Using cost functions that highlight both inner and outer vessel wall borders, the method combines the search for both borders into a single graph cut optimization. Our approach requires little user interaction and can robustly segment the carotid artery bifurcation. Experiments on 32 carotid arteries from 16 patients show good agreement between manual segmentation performed by an expert and our method. The mean relative area of overlap is more than 85% for both lumen and outer vessel wall. In addition, differences in measured wall thickness with respect to the manual annotations were smaller than the in-plane pixel size.