O. Lézoray and L. Grady, Image Processing and Analysis With Graphs: Theory and Practice (Digital Imaging and Computer Vision, 2012.

H. Winnemöller, S. C. Olsen, and B. Gooch, Real-time video abstraction, ACM Trans. Graph, vol.53

J. Chen, S. Paris, and F. Durand, Real-time edge-aware image processing with the bilateral grid, Proc. ACM SIGGRAPH, p.103, 2007.

S. Paris, Edge-Preserving Smoothing and Mean-Shift Segmentation of Video Streams, Proc. 10th Eur. Conf. Comput. Vis. (ECCV), pp.460-473, 2008.
DOI : 10.1007/978-3-540-88688-4_34

Y. Tarabalka, L. Brucker, A. Ivanoff, and J. C. Tilton, Shapeconstrained segmentation approach for arctic multiyear sea ice floe analysis, Proc. Int. Geosci. Remote Sens. Symp. (IGARSS), pp.4958-4961, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00729033

J. Shi and J. Malik, Motion segmentation and tracking using normalized cuts, Proc. 6th Int. Conf. Comput. Vis, pp.1154-1160, 1998.

D. Dementhon, Spatio-temporal segmentation of video by hierarchical mean shift analysis, Proc. Statist. Methods Video Process. Workshop (SMVP)

M. Grundmann, V. Kwatra, M. Han, and I. Essa, Efficient hierarchical graph-based video segmentation, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.2-3
DOI : 10.1109/CVPR.2010.5539893

R. Wolz, s i n g4 Dg r a p h cut segmentation: Application to ADNI, NeuroImage, issue.21, pp.109-118, 2010.

D. Cremers, F. Tischhauser, J. Weickert, and C. Schnorr, Diffusion snakes: Introducing statistical shape knowledge into the Mumford-Shah functional, International Journal of Computer Vision, vol.50, issue.3, pp.295-313, 2002.
DOI : 10.1023/A:1020826424915

M. Rousson and N. Paragios, Shape Priors for Level Set Representations, Proc. 7th Eur. Conf. Comput. Vis, pp.7-8
DOI : 10.1007/3-540-47967-8_6

P. Felzenszwalb, Representationa n dd e t e c t i o no fs h a p e si ni m a g e s, Ph.D. dissertation, Dept. Electr. Eng. Comput. Sci., Massachusetts Inst. Technol

T. Schoenemann and D. Cremers, Globally Optimal Image Segmentation with an Elastic Shape Prior, 2007 IEEE 11th International Conference on Computer Vision, pp.1-6
DOI : 10.1109/ICCV.2007.4408972

T. Schoenemann and D. Cremers, Globally optimal shape-based tracking in real-time, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-6
DOI : 10.1109/CVPR.2008.4587443

T. Riklin-raviv, K. V. Leemput, B. H. Menze, W. M. Wells, and P. , S eg m entation o f im age ens em b les v ia latent atlas es, Med. Image Anal, vol.45, pp.6-11

Y. Tarabalka, G. Charpiat, L. Brucker, and B. H. Menze, Enforcing Monotonous Shape Growth or Shrinkage in Video Segmentation, Procedings of the British Machine Vision Conference 2013
DOI : 10.5244/C.27.27
URL : https://hal.archives-ouvertes.fr/hal-00856634

Y. Boykov and V. Kolmogorov, An experimental comparison of mincut/max-flow algorithms for energy minimization in vision, IEEE Trans. Pattern Anal. Mach. Intell, vol.69

G. B. Dantzig and D. R. Fulkerson, 12. On the Max-Flow Min-Cut Theorem of Networks, Ann. Math. Studies, vol.8
DOI : 10.1515/9781400881987-013

A. V. Goldberg and R. E. Tarjan, A new approach to the maximum-flow problem, J. ACM,v o l, vol.34, issue.5

H. Ishikawa, Exact optimization for markov random fields with convex priors, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.25, issue.10, pp.1333-1336, 2003.
DOI : 10.1109/TPAMI.2003.1233908

A. Delong and Y. Boykov, Globally optimal segmentation of multiregion objects, Proc. 12th Int. Conf. Comput. Vis. (ICCV), pp.285-292, 2009.

K. Li, X. Wu, D. Z. Chen, and M. Sonka, Optimal surface segmentation in volumetric images?A graph-theoretic approach, IEEE Trans. Pattern Anal. Mach. Intell, vol.81, pp.1-1

A. Delong and Y. Boykov, A Scalable graph-cut algorithm for N-D grids, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2008.
DOI : 10.1109/CVPR.2008.4587464

J. Darbon, Global optimizationf o rfi r s to r d e rM a r k o vr a n d o mfi e l d s with submodular priors, Proc. 12th Int. Workshop Combinat. Image Anal, pp.2-2

L. Dice, Measure of the amount of ecological association between species, Ecology, vol.63

D. Haverkamp and C. Tsatsoulis, Using temporal information in an automated classification of summer, marginal ice zone imagery, IGARSS '96. 1996 International Geoscience and Remote Sensing Symposium, pp.0-9
DOI : 10.1109/IGARSS.1996.516260

D. P. Roy, P. E. Lewis, and C. O. Justice, Burned area mapping using multi-temporal moderate spatial resolution data???a bi-directional reflectance model-based expectation approach, Remote Sensing of Environment, vol.83, issue.1-2, pp.1-2, 2002.
DOI : 10.1016/S0034-4257(02)00077-9

J. B. Lewis, Fire mapping for managers in North Australian savanna; An object orientated classification model for MODIS imagery, Proc

L. Giglio, T. Loboda, D. P. Roy, B. Quayle, and C. O. Justice, An active-fire based burned area mapping algorithm for the MODIS sensor, Remote Sensing of Environment, vol.113, issue.2
DOI : 10.1016/j.rse.2008.10.006

P. Soille, Morphological Image Analysis,2 n de d .B e r l i n, 2003.

B. H. Menze, K. Van-leemput, D. Lashkari, M. Weber, N. Ayache et al., A Generative Model for Brain Tumor Segmentation in Multi-Modal Images, Proc. Med. Image Comput. Comput.-Assist
DOI : 10.1007/978-3-642-15745-5_19
URL : https://hal.archives-ouvertes.fr/hal-00813776

W. M. Wells, I. , W. E. Grimson, R. Kikinis, and F. A. Jolesz, Adaptive segmentation of MRI data, IEEE Transactions on Medical Imaging, vol.15, issue.4, pp.429-442, 1996.
DOI : 10.1109/42.511747

T. Kapur, W. E. Grimson, W. M. Wells, I. , and R. Kikinis, Segmentation of brain tissue from magnetic resonance images, Medical Image Analysis, vol.1, issue.2
DOI : 10.1016/S1361-8415(96)80008-9

F. G. Blankenberg, T h ei n fl u e n c eo fv o l u m e t r i ct u m o rd o u b l i n g time, DNA ploidy, and histologic grade on the survival of patients with intracranial astrocytomas, Amer. J. Neuroradiol, pp.1001-1012, 1995.

E. Konukoglu, Imageguidedpersonalizationofreaction-diffusion type tumor growth models using modified anisotropic Eikonal equations, IEEE Trans. Med. Imag, vol.91, pp.7-7