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

X. Artaechevarria, A. Munoz-barrutia, and C. Ortiz-de-solorzano, Combination Strategies in Multi-Atlas Image Segmentation: Application to Brain MR Data, IEEE Transactions on Medical Imaging, vol.28, issue.8, pp.1266-1277, 2009.
DOI : 10.1109/TMI.2009.2014372

L. Breiman, Random Forests, Mach. Learn, vol.45, 2001.

J. Eugenio-iglesias, M. R. Sabuncu, and K. Van-leemput, A unified framework for cross-modality multi-atlas segmentation of brain MRI. Medical Image Analysis, pp.1181-1191, 2013.

B. Glocker, A. Sotiras, N. Komodakis, and N. Paragios, Deformable Medical Image Registration: Setting the State of the Art with Discrete Methods, Annual Review of Biomedical Engineering, vol.13, issue.1, pp.219-244, 2011.
DOI : 10.1146/annurev-bioeng-071910-124649

URL : https://hal.archives-ouvertes.fr/hal-00858380

I. Isgum, M. Staring, A. Rutten, M. Prokop, M. A. Viergever et al., Multi-Atlas-Based Segmentation With Local Decision Fusion—Application to Cardiac and Aortic Segmentation in CT Scans, IEEE Transactions on Medical Imaging, vol.28, issue.7, pp.1000-1010, 2008.
DOI : 10.1109/TMI.2008.2011480

N. Komodakis, N. Paragios, and G. Tziritas, MRF Energy Minimization and Beyond via Dual Decomposition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.3, pp.531-552, 2011.
DOI : 10.1109/TPAMI.2010.108

URL : https://hal.archives-ouvertes.fr/hal-00856311

J. Kybic and M. Unser, Fast parametric elastic image registration, IEEE Transactions on Image Processing, vol.12, issue.11, pp.1427-1442, 2003.
DOI : 10.1109/TIP.2003.813139

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.90.2805

T. Rohlfing, Image Similarity and Tissue Overlaps as Surrogates for Image Registration Accuracy: Widely Used but Unreliable, IEEE Transactions on Medical Imaging, vol.31, issue.2, p.31, 2012.
DOI : 10.1109/TMI.2011.2163944

T. Rohlfing, D. Russakoff, and C. Maurer, Expectation Maximization Strategies for Multi-atlas Multi-label Segmentation, Lecture Notes in Computer Science, vol.2732, pp.210-221, 2003.
DOI : 10.1007/978-3-540-45087-0_18

T. Rohlfing, R. Brandt, R. Menzel, and C. Jr, Evaluation of atlas selection strategies for atlas-based image segmentation with application to confocal microscopy images of bee brains, NeuroImage, vol.21, issue.4, pp.1428-1442, 2004.
DOI : 10.1016/j.neuroimage.2003.11.010

D. Rueckert, I. Luke, C. Sonoda, D. L. Hayes, M. O. Hill et al., Nonrigid registration using free-form deformations: application to breast MR images, IEEE Transactions on Medical Imaging, vol.18, issue.8, pp.18712-721, 1999.
DOI : 10.1109/42.796284

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

M. Sdika, Combining atlas based segmentation and intensity classification with nearest neighbor transform and accuracy weighted vote, Medical Image Analysis, vol.14, issue.2, pp.219-226, 2010.
DOI : 10.1016/j.media.2009.12.004

URL : https://hal.archives-ouvertes.fr/hal-00617791