Colorectal polyp segmentation based on geodesic active contours with a shape-prior model

  • Authors:

  • Haiyong Xu;H. Donald Gage;Pete Santago;Yaorong Ge

  • Affiliations:

  • Department of Biomedical Engineering, Wake Forest University School of Biomedical Engineering and Sciences, Winston-Salem, NC;Department of Radiology, Wake Forest University School of Biomedical Engineering and Sciences, Winston-Salem, NC;Department of Biomedical Engineering, Wake Forest University School of Biomedical Engineering and Sciences, Winston-Salem, NC;Department of Biomedical Engineering, Wake Forest University School of Biomedical Engineering and Sciences, Winston-Salem, NC

  • Venue:
  • MICCAI'10 Proceedings of the Second international conference on Virtual Colonoscopy and Abdominal Imaging: computational challenges and clinical opportunities
  • Year:
  • 2010

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Abstract

Automated polyp segmentation is important both in measuring polyp size and in improving polyp detection performance in CTC. We present a polyp segmentation method that is based on the combination of geodesic active contours and a shape-prior model of polyps. To train the shape model, polyps identified by radiologists are grouped by morphologic characteristics. Each group of polyps is used for building a shape-prior model. Then the geodesic active contours method is employed to segment polyps constrained by this shape-prior model. This method can reliably segment polyp boundaries even where the image contrast is not sufficient to define a boundary between a polyp and its surrounding colon tissue. As a pilot study, we developed one polyp shape-prior model for sessile polyps that are located on a relatively flat colon wall. We use the model to segment similar polyps, and the results are evaluated visually.