Affine-Invariant Multi-reference Shape Priors for Active Contours

2006 ◽  
pp. 601-613 ◽  
Author(s):  
Alban Foulonneau ◽  
Pierre Charbonnier ◽  
Fabrice Heitz
Keyword(s):  
Active Contours ◽  
Affine Invariant ◽  
Shape Priors ◽  
Reference Shape

scholarly journals Multi-Reference Shape Priors for Active Contours

2008 ◽  
Vol 81 (1) ◽  
pp. 68-81 ◽  
Author(s):  
Alban Foulonneau ◽  
Pierre Charbonnier ◽  
Fabrice Heitz
Keyword(s):  
Active Contours ◽  
Shape Priors ◽  
Reference Shape

Affine-invariant geometric shape priors for region-based active contours

2006 ◽  
Vol 28 (8) ◽  
pp. 1352-1357 ◽  
Author(s):  
A. Foulonneau ◽  
P. Charbonnier ◽  
F. Heitz
Keyword(s):  
Active Contours ◽  
Geometric Shape ◽  
Affine Invariant ◽  
Shape Priors

scholarly journals Automatic Image Segmentation Using Active Contours with Univariate Marginal Distribution

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
I. Cruz-Aceves ◽  
J. G. Avina-Cervantes ◽  
J. M. Lopez-Hernandez ◽  
M. G. Garcia-Hernandez ◽  
M. Torres-Cisneros ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Active Contour ◽  
Marginal Distribution ◽  
Active Contours ◽  
Active Contour Model ◽  
Magnetic Resonance Images ◽  
Distribution Model ◽  
Shape Priors ◽  
Segmentation Method ◽  
Reference Shape

This paper presents a novel automatic image segmentation method based on the theory of active contour models and estimation of distribution algorithms. The proposed method uses the univariate marginal distribution model to infer statistical dependencies between the control points on different active contours. These contours have been generated through an alignment process of reference shape priors, in order to increase the exploration and exploitation capabilities regarding different interactive segmentation techniques. This proposed method is applied in the segmentation of the hollow core in microscopic images of photonic crystal fibers and it is also used to segment the human heart and ventricular areas from datasets of computed tomography and magnetic resonance images, respectively. Moreover, to evaluate the performance of the medical image segmentations compared to regions outlined by experts, a set of similarity measures has been adopted. The experimental results suggest that the proposed image segmentation method outperforms the traditional active contour model and the interactive Tseng method in terms of segmentation accuracy and stability.

scholarly journals Matching-constrained active contours with affine-invariant shape prior

2015 ◽  
Vol 132 ◽  
pp. 39-55 ◽  
Author(s):  
Junyan Wang ◽  
Sai-Kit Yeung ◽  
Kap Luk Chan
Keyword(s):  
Active Contours ◽  
Affine Invariant ◽  
Shape Prior ◽  
Invariant Shape
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