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.
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Xu, H., Gage, H.D., Santago, P., Ge, Y. (2011). Colorectal Polyp Segmentation Based on Geodesic Active Contours with a Shape-Prior Model. In: Yoshida, H., Cai, W. (eds) Virtual Colonoscopy and Abdominal Imaging. Computational Challenges and Clinical Opportunities. ABD-MICCAI 2010. Lecture Notes in Computer Science, vol 6668. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25719-3_19
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DOI: https://doi.org/10.1007/978-3-642-25719-3_19
Publisher Name: Springer, Berlin, Heidelberg
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