EPFL
 Biomedical Imaging GroupSTI
EPFL
  Publications
English only   BIG > Publications > Parametric Snakes


 CONTENTS
 Home Page
 News & Events
 People
 Publications
 Tutorials and Reviews
 Research
 Demos
 Download Algorithms

 DOWNLOAD
 PDF
 Postscript
 All BibTeX References

Texture-Driven Parametric Snakes for Semi-Automatic Image Segmentation

A. Badoual, M. Unser, A. Depeursinge

Computer Vision and Image Understanding, vol. 188, paper no. 102793, pp. 1-11, November 2019.



We present a texture-driven parametric snake for semi-automatic segmentation of a single and closed structure in an image. We propose a new energy functional that combines intensity and texture information. The two types of image information are balanced using Fisher's linear discriminant analysis. The framework can be used with any filter-based texture features. The parametric representation of the snake allows for easy and friendly user interaction while the framework can be trained on-the-fly from pixel collections provided by the user. We demonstrate the efficiency of the snake through an extensive validation on synthetic as well as on real data. Additionally, we show that the proposed snake is robust to noise and that it improves the segmentation performance when compared to an intensity-only scheme.


@ARTICLE(http://bigwww.epfl.ch/publications/badoual1904.html,
AUTHOR="Badoual, A. and Unser, M. and Depeursinge, A.",
TITLE="Texture-Driven Parametric Snakes for Semi-Automatic Image
        Segmentation",
JOURNAL="Computer Vision and Image Understanding",
YEAR="2019",
volume="188",
number="",
pages="1--11",
month="November",
note="paper no.\ 102793")

© 2019 Elsevier. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from Elsevier.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.