E. Eisenhauer, P. Therasse, J. Bogaerts, L. Schwartz, D. Sargent et al., New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1), European Journal of Cancer, vol.45, issue.2, pp.228-247, 2009.
DOI : 10.1016/j.ejca.2008.10.026

P. Y. Wen, D. R. Macdonald, D. A. Reardon, T. F. Cloughesy, A. G. Sorensen et al., Updated Response Assessment Criteria for High-Grade Gliomas: Response Assessment in Neuro-Oncology Working Group, Journal of Clinical Oncology, vol.28, issue.11, pp.1963-1972, 2010.
DOI : 10.1200/JCO.2009.26.3541

E. D. Angelini, O. Clatz, E. Mandonnet, E. Konukoglu, L. Capelle et al., Glioma Dynamics and Computational Models: A Review of Segmentation, Registration, and In Silico Growth Algorithms and their Clinical Applications, Current Medical Imaging Reviews, vol.3, issue.4, pp.262-276, 2007.
DOI : 10.2174/157340507782446241
URL : https://hal.archives-ouvertes.fr/inria-00616021

E. Mandonnet, S. Wait, L. Choi, and C. Teo, The importance of measuring the velocity of diameter expansion on MRI in upfront management of suspected WHO grade II glioma???????Case report, Neurochirurgie, vol.59, issue.2, pp.89-92, 2013.
DOI : 10.1016/j.neuchi.2013.02.005

B. Menze, M. Reyes, and K. Van-leemput, The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS), IEEE Transactions on Medical Imaging, vol.34, issue.10, pp.1-33, 2014.
DOI : 10.1109/TMI.2014.2377694
URL : https://hal.archives-ouvertes.fr/hal-00935640

D. Zikic, B. Glocker, E. Konukoglu, A. Criminisi, C. Demiralp et al., Decision Forests for Tissue-Specific Segmentation of High-Grade Gliomas in Multi-channel MR, MICCAI 2012, pp.369-376, 2012.
DOI : 10.1007/978-3-642-33454-2_46

N. J. Tustison, K. Shrinidhi, M. Wintermark, C. R. Durst, B. M. Kandel et al., Optimal Symmetric Multimodal Templates and Concatenated Random Forests for Supervised Brain Tumor Segmentation (Simplified) with ANTsR, Neuroinformatics, vol.12, issue.Pt 2, pp.1-17, 2014.
DOI : 10.1007/s12021-014-9245-2

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, MICCAI 2010, pp.151-159, 2010.
DOI : 10.1007/978-3-642-15745-5_19
URL : https://hal.archives-ouvertes.fr/hal-00813776

D. Kwon, R. T. Shinohara, H. Akbari, and C. Davatzikos, Combining Generative Models for Multifocal Glioma Segmentation and Registration, MICCAI 2014, pp.763-770, 2014.
DOI : 10.1007/978-3-319-10404-1_95

J. E. Iglesias and M. R. Sabuncu, Multi-atlas segmentation of biomedical images: A survey, Medical Image Analysis, vol.24, issue.1, 2015.
DOI : 10.1016/j.media.2015.06.012

T. Rohlfing, D. B. Russakoff, and C. R. Maurer-jr, Extraction and Application of Expert Priors to Combine Multiple Segmentations of Human Brain Tissue, MICCAI 2003, pp.578-585, 2003.
DOI : 10.1007/978-3-540-39903-2_71

R. A. Heckemann, J. V. Hajnal, P. Aljabar, D. Rueckert, and A. Hammers, Automatic anatomical brain MRI segmentation combining label propagation and decision fusion, NeuroImage, vol.33, issue.1, pp.115-126, 2006.
DOI : 10.1016/j.neuroimage.2006.05.061

P. Aljabar, R. A. Heckemann, A. Hammers, J. V. Hajnal, and D. Rueckert, Multi-atlas based segmentation of brain images: Atlas selection and its effect on accuracy, NeuroImage, vol.46, issue.3, pp.726-738, 2009.
DOI : 10.1016/j.neuroimage.2009.02.018

M. J. Cardoso, K. Leung, M. Modat, S. Keihaninejad, D. Cash et al., STEPS: Similarity and Truth Estimation for Propagated Segmentations and its application to hippocampal segmentation and brain parcelation, Medical Image Analysis, vol.17, issue.6, pp.671-684, 2013.
DOI : 10.1016/j.media.2013.02.006

F. Rousseau, P. A. Habas, and C. Studholme, A Supervised Patch-Based Approach for Human Brain Labeling, IEEE Transactions on Medical Imaging, vol.30, issue.10, pp.1852-1862, 2011.
DOI : 10.1109/TMI.2011.2156806
URL : https://hal.archives-ouvertes.fr/hal-00631458

P. Coupé, J. V. Manjón, V. Fonov, J. Pruessner, M. Robles et al., Patch-based segmentation using expert priors: Application to hippocampus and ventricle segmentation, NeuroImage, vol.54, issue.2, pp.940-954, 2011.
DOI : 10.1016/j.neuroimage.2010.09.018

J. E. Romero, J. V. Manjón, J. Tohka, P. Coupé, and M. Robles, NABS: non-local automatic brain hemisphere segmentation, Magnetic resonance imaging, 2015.
DOI : 10.1016/j.mri.2015.02.005
URL : https://hal.archives-ouvertes.fr/hal-01116696

A. J. Asman and B. Landman, Out-of-atlas labeling: A multi-atlas approach to cancer segmentation, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp.1236-1239, 2012.
DOI : 10.1109/ISBI.2012.6235785

M. J. Cardoso, C. H. Sudre, M. Modat, and S. Ourselin, Template-Based Multimodal Joint Generative Model of Brain Data, Information Processing in Medical Imaging, pp.17-29, 2015.
DOI : 10.1007/978-3-319-19992-4_2

M. Svensén and C. M. Bishop, Robust Bayesian mixture modelling, Neurocomputing, vol.64, pp.235-252, 2005.
DOI : 10.1016/j.neucom.2004.11.018

N. Shiee, P. Bazin, J. L. Cuzzocreo, A. Blitz, and D. L. Pham, Segmentation of Brain Images Using Adaptive Atlases with Application to Ventriculomegaly, Information Processing in Medical Imaging, pp.1-12, 2011.
DOI : 10.1007/978-3-642-22092-0_1

J. Mazziotta, A. Toga, A. Evans, P. Fox, J. Lancaster et al., A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM), Philosophical Transactions of the Royal Society B: Biological Sciences, vol.356, issue.1412, pp.1293-1322, 2001.
DOI : 10.1098/rstb.2001.0915

C. Liu and D. B. Rubin, ML estimation of the t distribution using EM and its extensions, ECM and ECME, Statistica Sinica, vol.5, issue.1, pp.19-39, 1995.

C. Wachinger, M. Brennan, G. C. Sharp, and P. Gol-land, On the Importance of Location and Features for the Patch-Based Segmentation of Parotid Glands, MICCAI Workshop on Image-Guided Adaptive Radiation Therapy, p.3472, 2014.

S. Larjavaara, R. Mäntylä, T. Salminen, H. Haapasalo, J. Raitanen et al., Incidence of gliomas by anatomic location, Neuro-Oncology, vol.9, issue.3, pp.319-325, 2007.
DOI : 10.1215/15228517-2007-016

H. Duffau and L. Capelle, Preferential brain locations of low-grade gliomas, Cancer, vol.991, issue.12, pp.2622-2626, 2004.
DOI : 10.1002/cncr.20297

S. Parisot, H. Duffau, S. Chemouny, and N. Paragios, Graph Based Spatial Position Mapping of Low-Grade Gliomas, MICCAI 2011, pp.508-515, 2011.
DOI : 10.1007/978-3-642-04268-3_83
URL : https://hal.archives-ouvertes.fr/hal-00775865

W. Bai, W. Shi, D. P. O-'regan, T. Tong, H. Wang et al., A probabilistic patch-based label fusion model for multi-atlas segmentation with registration refinement: application to cardiac MR images, Medical Imaging IEEE Transactions on, vol.32, issue.7, pp.1302-1315, 2013.

M. R. Sabuncu, B. T. Yeo, K. Van-leemput, B. Fischl, and P. Golland, A Generative Model for Image Segmentation Based on Label Fusion, IEEE Transactions on Medical Imaging, vol.29, issue.10, pp.1714-1729, 2010.
DOI : 10.1109/TMI.2010.2050897

Y. Zhang, M. Brady, and S. Smith, Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm, IEEE Transactions on Medical Imaging, vol.20, issue.1, pp.45-57, 2001.
DOI : 10.1109/42.906424

C. Wachinger and P. Golland, Atlas-Based Under-Segmentation, MICCAI 2014, pp.315-322, 2014.
DOI : 10.1007/978-3-319-10404-1_40

M. Muja and D. G. Lowe, Scalable Nearest Neighbor Algorithms for High Dimensional Data Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.36, 2014.

N. Cordier, B. Menze, H. Delingette, and N. Ayache, Patch-based Segmentation of Brain Tissues, MICCAI Challenge on Multimodal Brain Tumor Segmentation, pp.6-17, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00917084

D. H. Ye, D. Zikic, B. Glocker, A. Criminisi, and E. Konukoglu, Modality Propagation: Coherent Synthesis of Subject-Specific Scans with Data-Driven Regularization, MICCAI 2013, pp.606-613, 2013.
DOI : 10.1007/978-3-642-40811-3_76