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Efficient Shape Priors for Spline-Based Snakes.

Authors :
Delgado-Gonzalo R
Schmitter D
Uhlmann V
Unser M
Source :
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society [IEEE Trans Image Process] 2015 Nov; Vol. 24 (11), pp. 3915-26.
Publication Year :
2015

Abstract

Parametric active contours are an attractive approach for image segmentation, thanks to their computational efficiency. They are driven by application-dependent energies that reflect the prior knowledge on the object to be segmented. We propose an energy involving shape priors acting in a regularization-like manner. Thereby, the shape of the snake is orthogonally projected onto the space that spans the affine transformations of a given shape prior. The formulation of the curves is continuous, which provides computational benefits when compared with landmark-based (discrete) methods. We show that this approach improves the robustness and quality of spline-based segmentation algorithms, while its computational overhead is negligible. An interactive and ready-to-use implementation of the proposed algorithm is available and was successfully tested on real data in order to segment Drosophila flies and yeast cells in microscopic images.

Details

Language :
English
ISSN :
1941-0042
Volume :
24
Issue :
11
Database :
MEDLINE
Journal :
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Publication Type :
Academic Journal
Accession number :
26353353
Full Text :
https://doi.org/10.1109/TIP.2015.2457335