Image Segmentation Using Active Contours: Calculus of Variations or Shape Gradients?, SIAM Journal on Applied Mathematics, vol.63, issue.6, pp.2128-2154, 2003. ,
DOI : 10.1137/S0036139902408928
URL : https://hal.archives-ouvertes.fr/inria-00072105
Unsupervised Variational Image Segmentation/Classification Using a Weibull Observation Model, IEEE Transactions on Image Processing, vol.15, issue.11, pp.3431-3439, 2006. ,
DOI : 10.1109/TIP.2006.881961
Fast and Fully Automatic 3-D Echocardiographic Segmentation Using B-Spline Explicit Active Surfaces: Feasibility Study and Validation in a Clinical Setting, Ultrasound in Medicine & Biology, vol.39, issue.1, pp.89-101, 2013. ,
DOI : 10.1016/j.ultrasmedbio.2012.08.008
URL : https://hal.archives-ouvertes.fr/hal-00796930
Implicit active contours for ultrasound images segmentation driven by phase information and local maximum likelihood, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.138-147, 2011. ,
DOI : 10.1109/ISBI.2011.5872486
URL : https://hal.archives-ouvertes.fr/hal-00586401
Geodesic active contours, Proceedings of IEEE International Conference on Computer Vision, pp.61-79, 1997. ,
DOI : 10.1109/ICCV.1995.466871
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.21.2196
Active contours without edges, IEEE Transactions on Image Processing, vol.10, issue.2, pp.266-277, 2001. ,
DOI : 10.1109/83.902291
The monogenic signal, IEEE Transactions on Signal Processing, vol.49, issue.12, pp.3136-3144, 2001. ,
DOI : 10.1109/78.969520
Geometric shape priors for region-based active contours, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), pp.413-429, 2003. ,
DOI : 10.1109/ICIP.2003.1247269
Combining Registration and Minimum Surfaces for the Segmentation of the Left Ventricle in Cardiac Cine MR Images, MICCAI, 2009. ,
DOI : 10.1007/978-3-642-04271-3_110
Snakes: Active contour models, International Journal of Computer Vision, vol.5, issue.6035, pp.321-331, 1988. ,
DOI : 10.1007/BF00133570
Symmetry and asymmetry from local phase, Tenth Australian Joint Conference on Artificial Intelligence, pp.2-4, 1997. ,
Localizing Region-Based Active Contours, IEEE Transactions on Image Processing, vol.17, issue.11, pp.2029-2039, 2008. ,
DOI : 10.1109/TIP.2008.2004611
Constructing simple stable descriptions for image partitioning, International Journal of Computer Vision, vol.1, issue.2, pp.73-102, 1989. ,
DOI : 10.1007/BF00054839
Segmentation of Left Ventricle in Cardiac Cine MRI: An Automatic Image-Driven Method, Functional Imaging and Modeling of the Heart, pp.339-347, 2009. ,
DOI : 10.1007/978-3-642-01932-6_37
2D+ t acoustic boundary detection in echocardiography, pp.21-30, 2000. ,
Optimal approximations by piecewise smooth functions and associated variational problems, Communications on Pure and Applied Mathematics, vol.3, issue.5, pp.577-685, 1989. ,
DOI : 10.1002/cpa.3160420503
A variational approach for the segmentation of the left ventricle in cardiac image analysis, International Journal of Computer Vision, vol.50, issue.3, pp.345-362, 2002. ,
DOI : 10.1023/A:1020882509893
Geodesic active regions and level set methods for supervised texture segmentation, International Journal of Computer Vision, vol.46, issue.3, pp.223-247, 2002. ,
DOI : 10.1023/A:1014080923068
Automated Left Ventricular Segmentation in Cardiac MRI, IEEE Transactions on Biomedical Engineering, vol.53, issue.7, pp.1425-1428, 2006. ,
DOI : 10.1109/TBME.2006.873684
A review of segmentation methods in short axis cardiac MR images, Medical Image Analysis, vol.15, issue.2, pp.169-184, 2011. ,
DOI : 10.1016/j.media.2010.12.004
URL : https://hal.archives-ouvertes.fr/hal-00551034
Feature detection from echocardiography images using local phase information. Medical Image Understanding and Analysis, 2008. ,
Level set methods and fast marching methods : evolving interfaces in computational geometry, fluid mechanics, computer vision, and materials science, 1999. ,