Functional optimization for fair surface design
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International Journal of Computer Vision
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Implicit fairing of irregular meshes using diffusion and curvature flow
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Anisotropic geometric diffusion in surface processing
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Fast visualization of plane-like structures in voxel data
Proceedings of the conference on Visualization '02
Statistical Study on Cortical Sulci of Human Brains
IPMI '01 Proceedings of the 17th International Conference on Information Processing in Medical Imaging
Any open bounded subset of Rn has the same homotopy type than its medial axis
SM '03 Proceedings of the eighth ACM symposium on Solid modeling and applications
Estimating the tensor of curvature of a surface from a polyhedral approximation
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
A Formal Classification of 3D Medial Axis Points and Their Local Geometry
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Robust Feature Detection and Local Classification for Surfaces Based on Moment Analysis
IEEE Transactions on Visualization and Computer Graphics
Defining and computing curve-skeletons with medial geodesic function
SGP '06 Proceedings of the fourth Eurographics symposium on Geometry processing
Computing Multiscale Curve and Surface Skeletons of Genus 0 Shapes Using a Global Importance Measure
IEEE Transactions on Visualization and Computer Graphics
Segmenting simplified surface skeletons
DGCI'08 Proceedings of the 14th IAPR international conference on Discrete geometry for computer imagery
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We present a method for computing a surface classifier that can be used to detect convex ridges on voxel sur- faces extracted from 3D scans. In contrast to classical approaches based on (discrete) curvature computations, which can be sensitive to various types of noise, we propose here a new method that detects convex ridges on such surfaces, based on the computation of the surface's 3D skeleton. We use a suitable robust, noise-resistant skeletonization algorithm to extract the full 3D skeleton of the given surface, and subsequently compute a surface classifier that separates convex ridges from quasi-flat regions, using the feature points of the simplified skeleton. We demonstrate our method on voxel surfaces extracted from actual anatomical scans, with a focus on cortical surfaces, and compare our results with curvature-based classifiers. As a second application of the 3D skeleton, we show how a partitioning of the brain skeleton can be used in a preprocessing step for the brain surface analysis.