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

机译:基于大地测量环的曲率图,用于CT结肠造影中的息肉检测

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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.
机译:现有的息肉检测方法严重依赖于基于曲率的特征来区分病变。但是,由于曲率是局部特征和二阶微分量,因此仅检查一点处的曲率是不够的。在本文中,我们建议使用曲率图检查候选点周围的局部邻域。使用表面贴片的测地线质心预先确定该候选点,该表面贴片的顶点具有与凸形凸起相对应的正点曲率值的顶点。然后围绕该候选点构造测地线环,并累积这些环周围的点曲率以生成曲率图。据此,可以计算出给定邻域半径的​​累积形状属性S,并将其用于识别通常具有较高S值的球状息肉及其对应的“颈部”区域。我们显示,S> 0.48的阈值足以区分息肉和非息肉,对球状息肉> 10mm的敏感性和特异性为100%。

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