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Finding the Minimum-Cost Path Without Cutting Corners

  • R. Joop van Heekeren
  • Frank G. A. Faas
  • Lucas J. van Vliet
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4522)

Abstract

Applying a minimum-cost path algorithm to find the path through the bottom of a curvilinear valley yields a biased path through the inside of a corner. DNA molecules, blood vessels, and neurite tracks are examples of string-like (network) structures, whose minimum-cost path is cutting through corners and is less flexible than the underlying centerline. Hence, the path is too short and its shape too stiff, which hampers quantitative analysis. We developed a method which solves this problem and results in a path whose distance to the true centerline is more than an order of magnitude smaller in areas of high curvature. We first compute an initial path. The principle behind our iterative algorithm is to deform the image space, using the current path in such a way that curved string-like objects are straightened before calculating a new path. A damping term in the deformation is needed to guarantee convergence of the method.

Keywords

Persistence Length Eikonal Equation High Contrast Image Pattern Recognition Letter Fast March 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • R. Joop van Heekeren
    • 1
  • Frank G. A. Faas
    • 1
  • Lucas J. van Vliet
    • 1
  1. 1.Quantitative Imaging Group, Delft University of TechnologyThe Netherlands

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