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2006

Global Segmentation and Curvature Analysis of Volumetric Data Sets Using Trivariate B-Spline Functions

8 years 11 months ago
Global Segmentation and Curvature Analysis of Volumetric Data Sets Using Trivariate B-Spline Functions
This paper presents a method to globally segment volumetric images into regions that contain convex or concave (elliptic) iso-surfaces, planar or cylindrical (parabolic) iso-surfaces, and volumetric regions with saddlelike (hyperbolic) iso-surfaces, regardless of the value of the iso-surface level. The proposed scheme relies on a novel approach to globally compute, bound, and analyze the Gaussian and mean curvatures of an entire volumetric data set, using a trivariate B-spline volumetric representation. This scheme derives a new differential scalar field for a given volumetric scalar field, which could easily be adapted to other differential properties. Moreover, this scheme can set the basis for more precise and accurate segmentation of data sets targeting the identification of primitive parts. Since the proposed scheme employs piecewise continuous functions, it is precise and insensitive to aliasing.
Octavian Soldea, Gershon Elber, Ehud Rivlin
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2006
Where PAMI
Authors Octavian Soldea, Gershon Elber, Ehud Rivlin
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