Heuristically driven front propagation for geodesic paths extraction

Authors:
Gabriel Peyré;Laurent Cohen
Affiliations:
CMAP, UMR CNRS 7641, École Polytechnique, Palaiseau, France;CEREMADE, UMR CNRS 7534, Universite Paris Dauphine, Paris, France
Venue:
VLSM'05 Proceedings of the Third international conference on Variational, Geometric, and Level Set Methods in Computer Vision
Year:
2005

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Abstract

In this paper we present a simple modification of the Fast Marching algorithm to speed up the computation using a heuristic. This modification leads to an algorithm that is similar in spirit to the A* algorithm used in artificial intelligence. Using a heuristic allows to extract geodesics from a single source to a single goal very quickly and with a low memory requirement. Any application that needs to compute a lot of geodesic paths can gain benefits from our algorithm. The computational saving is even more important for 3D medical images with tubular structures and for higher dimensional data.