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Geodesic-ring based curvature maps for polyp detection in CT colonography

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Seghouane, Abd-Krim
Ong, Ju

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IEEE Signal Processing Society

Abstract

Existing polyp detection methods rely heavily on curvature-based characteristics to differentiate between lesions. However, as curvature is a local feature and a second order differential quantity, simply inspecting the curvature at a point is not sufficient. In this paper, we propose to inspect a local neighbourhood around a candidate point using curvature maps. This candidate point is pre-identified using the geodesic centroid of a surface patch containing vertices with positive point curvature values corresponding to convex shaped protrusions. Geodesic rings are then constructed around this candidate point and point curvatures around these rings are accumulated to produce curvature maps. From this, a cumulative shape property, S for a given neighbourhood radius can be computed and used for identifying bulbous polyps which typically have a high S value, and its corresponding'neck'region. We show that a threshold value of S > 0.48 is sufficient to discriminate between polyps and non polyps with 100% sensitivity and specificity for bulbous polyps > 10mm.

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Proceedings of IEEE International Conference on Image Processing 2010

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2037-12-31