Analysis of kernel method for surface curvature estimation

We examine a method of curvature estimation that computes the curvature directly from three dimensional data. We refer to this as the kernel method of curvature estimation and our experiments indicate that several parameters be modified from those originally suggested to achieve more accurate and reliable results. This improved performance is essential for analysis of medical volume data by computer aided diagnosis algorithms, many of which use curvature estimation for shape computations and pattern recognition. We also examine cases in which the kernel method yields inaccurate responses based on specific topologies. D 2004 CARS and Elsevier B.V. All rights reserved.