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


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

 DOWNLOAD
 PDF
 Postscript
 All BibTeX References

Locally Refinable Parametric Snakes

A. Badoual, D. Schmitter, M. Unser

Proceedings of the 2015 IEEE International Conference on Image Processing (ICIP'15), Québec QC, Canada, September 27-30, 2015, paper no. TEC-P21.2.



Shape segmentation is an active field of research in biomedical imaging. In this context, we present a new parameterization of a snake that is locally refinable. We introduce the possibility of locally increasing the approximation power of the parametric model by inserting basis functions at a specific location. This is controlled by a user-interface that permits the refinement of an initial segmentation around an anchor position selected by a user. Our approach relies on scaling functions that satisfy the refinement relation and are related to wavelets. We also derive explicit formulas for the energy functions associated to our new parameterization. We demonstrate the accuracy of our snake and its robustness under noisy conditions on phantom data. We also present segmentation results on real cell images, which are our main target. The algorithm is made freely available as a plugin for the open source platform Icy.


@INPROCEEDINGS(http://bigwww.epfl.ch/publications/badoual1501.html,
AUTHOR="Badoual, A. and Schmitter, D. and Unser, M.",
TITLE="Locally Refinable Parametric Snakes",
BOOKTITLE="Proceedings of the 2015 {IEEE} International Conference on
        Image Processing ({ICIP'15})",
YEAR="2015",
editor="",
volume="",
series="",
pages="",
address="Qu{\'{e}}bec QC, Canada",
month="September 27-30,",
organization="",
publisher="",
note="paper no.\ TEC-P21.2")

© 2015 IEEE. 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 IEEE.
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.