Riemannian mean curvature flow

Authors:
Raúl San José Estépar;Steve Haker;Carl-Fredrik Westin
Affiliations:
Laboratory of Mathematics in Imaging, Brigham and Women’s Hosptial, Harvard Medical School, Boston, MA;Laboratory of Mathematics in Imaging, Brigham and Women’s Hosptial, Harvard Medical School, Boston, MA;Laboratory of Mathematics in Imaging, Brigham and Women’s Hosptial, Harvard Medical School, Boston, MA
Venue:
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
Year:
2005

Citing 2
Cited 0

Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations

Journal of Computational Physics
Geodesic Active Contours

International Journal of Computer Vision

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Abstract

In this paper we explicitly derive a level set formulation for mean curvature flow in a Riemannian metric space. This extends the traditional geodesic active contour framework which is based on conformal flows. Curve evolution for image segmentation can be posed as a Riemannian evolution process where the induced metric is related to the local structure tensor. Examples on both synthetic and real data are shown.