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International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition

EMMCVPR 2017: Energy Minimization Methods in Computer Vision and Pattern Recognition pp 499–513Cite as

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

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10746))

Abstract

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.

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Acknowledgement

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

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Authors and Affiliations

  1. CEREMADE, PSL Research University, Université Paris Dauphine, CNRS, UMR 7534, 75016, Paris, France

    Emmanuel Cohen & Laurent D. Cohen

  2. Institut Langevin, PSL Research University, ESPCI ParisTech, CNRS, UMR 7587, INSERM U979, 75005, Paris, France

    Emmanuel Cohen, Thomas Deffieux & Mickael Tanter

Authors
  1. Emmanuel Cohen
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  2. Laurent D. Cohen
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  3. Thomas Deffieux
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  4. Mickael Tanter
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Corresponding author

Correspondence to Emmanuel Cohen .

Editor information

Editors and Affiliations

  1. Ca’ Foscari University of Venice, Venice, Italy

    Marcello Pelillo

  2. University of York, York, United Kingdom

    Edwin Hancock

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Cohen, E., Cohen, L.D., Deffieux, T., Tanter, M. (2018). An Isotropic Minimal Path Based Framework for Segmentation and Quantification of Vascular Networks. In: Pelillo, M., Hancock, E. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2017. Lecture Notes in Computer Science(), vol 10746. Springer, Cham. https://doi.org/10.1007/978-3-319-78199-0_33

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  • DOI: https://doi.org/10.1007/978-3-319-78199-0_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-78198-3

  • Online ISBN: 978-3-319-78199-0

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