An Isotropic Minimal Path Based Framework for Segmentation and Quantification of Vascular Networks

  • Emmanuel CohenEmail author
  • Laurent D. Cohen
  • Thomas Deffieux
  • Mickael Tanter
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10746)


Minimal path approaches for image analysis aim to extract curves minimizing an energy functional. The energy of a path corresponds to its weighted curve length according to a relevant metric function. In this study, we design a binary isotropic metric model with the use of a Hessian-based vascular enhancement filter in order to extract geometrical features from vascular networks. We introduce a constrained keypoint search method able to extract subpixel vessel centrelines, diameters and bifurcations. Experiments on retinal images demonstrated that the proposed framework achieves similar even better segmentation performances as compared with methods using more sophisticated metric designs.



We would like to particularly thank Dr. Da Chen for his precious help and advice.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Emmanuel Cohen
    • 1
    • 2
    Email author
  • Laurent D. Cohen
    • 1
  • Thomas Deffieux
    • 2
  • Mickael Tanter
    • 2
  1. 1.CEREMADE, PSL Research University, Université Paris Dauphine, CNRS, UMR 7534ParisFrance
  2. 2.Institut Langevin, PSL Research University, ESPCI ParisTech, CNRS, UMR 7587, INSERM U979ParisFrance

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