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

J. Barnes, J. Foster, R. G. Boyes, T. Pepple, E. K. Moore et al., A comparison of methods for the automated calculation of volumes and atrophy rates in the hippocampus, NeuroImage, vol.40, issue.4, pp.1655-1671, 2008.
DOI : 10.1016/j.neuroimage.2008.01.012

N. Bernasconi, A. Bernasconi, Z. Caramanos, S. B. Antel, F. Andermann et al., Mesial temporal damage in temporal lobe epilepsy: a volumetric MRI study of the hippocampus, amygdala and parahippocampal region, Brain, vol.126, issue.2, pp.462-469, 2003.
DOI : 10.1093/brain/awg034

J. D. Bremner, M. Narayan, E. R. Anderson, L. H. Staib, H. L. Miller et al., Hippocampal Volume Reduction in Major Depression, American Journal of Psychiatry, vol.157, issue.1, pp.115-118, 2000.
DOI : 10.1176/ajp.157.1.115

J. D. Bremner, P. Randall, T. M. Scott, R. A. Bronen, J. P. Seibyl et al., MRI-based measurement of hippocampal volume in patients with combat-related posttraumatic stress disorder, Am J Psychiatry, vol.152, pp.973-981, 1995.

T. Brox, O. Kleinschmidt, and D. Cremers, Efficient Nonlocal Means for Denoising of Textural Patterns, IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, pp.1083-1092, 2008.
DOI : 10.1109/TIP.2008.924281

A. Buades, B. Coll, and J. M. Morel, A Non-Local Algorithm for Image Denoising, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.60-65, 2005.
DOI : 10.1109/CVPR.2005.38

C. Buss, C. Lord, M. Wadiwalla, D. H. Hellhammer, S. J. Lupien et al., Maternal Care Modulates the Relationship between Prenatal Risk and Hippocampal Volume in Women But Not in Men, Journal of Neuroscience, vol.27, issue.10, pp.2592-2595, 2007.
DOI : 10.1523/JNEUROSCI.3252-06.2007

M. Chupin, A. R. Mukuna-bantumbakulu, D. Hasboun, E. Bardinet, S. Baillet et al., Anatomically constrained region deformation for the automated segmentation of the hippocampus and the amygdala: Method and validation on controls and patients with Alzheimer???s disease, NeuroImage, vol.34, issue.3, pp.996-1019, 2007.
DOI : 10.1016/j.neuroimage.2006.10.035

D. L. Collins, C. J. Holmes, T. M. Peters, and A. C. Evans, Automatic 3-D model-based neuroanatomical segmentation, Human Brain Mapping, vol.16, issue.2, pp.190-208, 1995.
DOI : 10.1002/hbm.460030304

D. L. Collins and J. C. Pruessner, Towards accurate, automatic segmentation of the hippocampus and amygdala from MRI by augmenting ANIMAL with a template library and label fusion, NeuroImage, vol.52, issue.4, 2010.
DOI : 10.1016/j.neuroimage.2010.04.193

P. Coupe, J. V. Manjon, E. Gedamu, D. Arnold, M. Robles et al., Robust Rician noise estimation for MR images, Medical Image Analysis, vol.14, issue.4, pp.483-493, 2010.
DOI : 10.1016/j.media.2010.03.001

URL : https://hal.archives-ouvertes.fr/inserm-00486495

P. Coupe, P. Yger, S. Prima, P. Hellier, C. Kervrann et al., An Optimized Blockwise Nonlocal Means Denoising Filter for 3-D Magnetic Resonance Images, IEEE Transactions on Medical Imaging, vol.27, issue.4, pp.425-441, 2008.
DOI : 10.1109/TMI.2007.906087

URL : https://hal.archives-ouvertes.fr/inserm-00169658

A. Criminisi, P. Perez, and K. Toyama, Region Filling and Object Removal by Exemplar-Based Image Inpainting, IEEE Transactions on Image Processing, vol.13, issue.9, pp.1200-1212, 2004.
DOI : 10.1109/TIP.2004.833105

S. Duchesne, J. Pruessner, and D. L. Collins, Appearance-Based Segmentation of Medial Temporal Lobe Structures, NeuroImage, vol.17, issue.2, pp.515-531, 2002.
DOI : 10.1006/nimg.2002.1188

A. A. Efros and W. T. Freeman, Image quilting for texture synthesis and transfer, Proceedings of the 28th annual conference on Computer graphics and interactive techniques , SIGGRAPH '01, pp.341-346, 2001.
DOI : 10.1145/383259.383296

B. Fischl, D. H. Salat, E. Busa, M. Albert, M. Dieterich et al., Whole Brain Segmentation, Neuron, vol.33, issue.3, pp.341-355, 2002.
DOI : 10.1016/S0896-6273(02)00569-X

A. Ghanei, H. Soltanian-zadeh, and J. P. Windham, Segmentation of the hippocampus from brain MRI using deformable contours, Computerized Medical Imaging and Graphics, vol.22, issue.3, pp.203-216, 1998.
DOI : 10.1016/S0895-6111(98)00026-3

I. S. Gousias, D. Rueckert, R. A. Heckemann, L. E. Dyet, J. P. Boardman et al., Automatic segmentation of brain MRIs of 2-year-olds into 83 regions of interest, NeuroImage, vol.40, issue.2, pp.672-684, 2008.
DOI : 10.1016/j.neuroimage.2007.11.034

A. Hammers, R. Heckemann, M. J. Koepp, J. S. Duncan, J. V. Hajnal et al., Automatic detection and quantification of hippocampal atrophy on MRI in temporal lobe epilepsy: A proof-of-principle study, NeuroImage, vol.36, issue.1, pp.38-47, 2007.
DOI : 10.1016/j.neuroimage.2007.02.031

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

S. Hu and D. L. Collins, Joint level-set shape modeling and appearance modeling for brain structure segmentation, NeuroImage, vol.36, issue.3, pp.672-683, 2007.
DOI : 10.1016/j.neuroimage.2006.12.048

K. Huang, D. Zhang, and K. Wang, Non-local means denoising algorithm accelerated by GPU, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, 2009.

C. R. Jack, . Jr, R. C. Petersen, Y. Xu, P. C. O-'brien et al., Rates of hippocampal atrophy correlate with change in clinical status in aging and AD, Neurology, vol.55, issue.4, pp.484-489, 2000.
DOI : 10.1212/WNL.55.4.484

C. Kervrann and J. Boulanger, Local Adaptivity to Variable Smoothness for Exemplar-Based Image Regularization and Representation, International Journal of Computer Vision, vol.27, issue.2, pp.45-69, 2008.
DOI : 10.1007/s11263-007-0096-2

J. M. Lotjonen, R. Wolz, J. R. Koikkalainen, L. Thurfjell, G. Waldemar et al., Fast and robust multi-atlas segmentation of brain magnetic resonance images, NeuroImage, vol.49, issue.3, pp.2352-2365, 2010.
DOI : 10.1016/j.neuroimage.2009.10.026

J. V. Manjon, P. Coupe, L. Marti-bonmati, D. L. Collins, and M. Robles, Adaptive non-local means denoising of MR images with spatially varying noise levels, Journal of Magnetic Resonance Imaging, vol.17, issue.1, pp.192-203, 2010.
DOI : 10.1002/jmri.22003

URL : https://hal.archives-ouvertes.fr/inserm-00454564

J. C. Mazziotta, A. W. Toga, A. Evans, P. Fox, and J. Lancaster, A Probabilistic Atlas of the Human Brain: Theory and Rationale for Its Development, NeuroImage, vol.2, issue.2, pp.89-101, 1995.
DOI : 10.1006/nimg.1995.1012

R. A. Morey, C. M. Petty, Y. Xu, J. P. Hayes, H. R. Wagner et al., A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes, NeuroImage, vol.45, issue.3, pp.855-866, 2009.
DOI : 10.1016/j.neuroimage.2008.12.033

J. H. Morra, Z. Tu, L. G. Apostolova, A. E. Green, C. Avedissian et al., Validation of a fully automated 3D hippocampal segmentation method using subjects with Alzheimer's disease mild cognitive impairment, and elderly controls, NeuroImage, vol.43, issue.1, pp.59-68, 2008.
DOI : 10.1016/j.neuroimage.2008.07.003

S. M. Nestor, R. Rupsingh, M. Borrie, M. Smith, V. Accomazzi et al., Ventricular enlargement as a possible measure of Alzheimer's disease progression validated using the Alzheimer's disease neuroimaging initiative database, Brain, vol.131, issue.9, pp.2443-2454, 2008.
DOI : 10.1093/brain/awn146

L. G. Nyul and J. K. Udupa, <title>Standardizing the MR image intensity scales: making MR intensities have tissue-specific meaning</title>, Medical Imaging 2000: Image Display and Visualization, pp.496-504, 2000.
DOI : 10.1117/12.383076

P. Xavier-de-fontes, F. Andrade-barroso, G. Coupé, P. Hellier, and P. , Real time ultrasound image denoising, Journal of Real-Time Image Processing, 2010.
DOI : 10.1007/s11554-010-0158-5

URL : https://hal.archives-ouvertes.fr/inria-00476122

K. M. Pohl, S. Bouix, M. Nakamura, T. Rohlfing, R. W. Mccarley et al., A Hierarchical Algorithm for MR Brain Image Parcellation, IEEE Transactions on Medical Imaging, vol.26, issue.9, pp.1201-1212, 2007.
DOI : 10.1109/TMI.2007.901433

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2768067

M. Protter, M. Elad, H. Takeda, and P. Milanfar, Generalizing the Nonlocal-Means to Super-Resolution Reconstruction, IEEE Transactions on Image Processing, vol.18, issue.1, pp.36-51, 2009.
DOI : 10.1109/TIP.2008.2008067

J. C. Pruessner, L. M. Li, W. Serles, M. Pruessner, D. L. Collins et al., Volumetry of Hippocampus and Amygdala with High-resolution MRI and Three-dimensional Analysis Software: Minimizing the Discrepancies between Laboratories, Cerebral Cortex, vol.10, issue.4, pp.433-442, 2000.
DOI : 10.1093/cercor/10.4.433

T. Rohlfing, R. Brandt, R. Menzel, C. R. Maurer, and . 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

R. Schonmeyer, D. Prvulovic, A. Rotarska-jagiela, C. Haenschel, and D. E. Linden, Automated segmentation of lateral ventricles from human and primate magnetic resonance images using cognition network technology, Magnetic Resonance Imaging, vol.24, issue.10, pp.1377-1387, 2006.
DOI : 10.1016/j.mri.2006.08.013

D. Shen, S. Moffat, S. M. Resnick, and C. Davatzikos, Measuring Size and Shape of the Hippocampus in MR Images Using a Deformable Shape Model, NeuroImage, vol.15, issue.2, pp.422-434, 2002.
DOI : 10.1006/nimg.2001.0987

M. R. Siadat, H. Soltanian-zadeh, and K. V. Elisevich, Knowledge-based localization of hippocampus in human brain MRI, Computers in Biology and Medicine, vol.37, issue.9, pp.1342-1360, 2007.
DOI : 10.1016/j.compbiomed.2006.12.010

J. G. Sled, A. P. Zijdenbos, and A. C. Evans, A nonparametric method for automatic correction of intensity nonuniformity in MRI data, IEEE Transactions on Medical Imaging, vol.17, issue.1, pp.87-97, 1998.
DOI : 10.1109/42.668698

P. Tanskanen, J. M. Veijola, U. K. Piippo, M. Haapea, J. A. Miettunen et al., Hippocampus and amygdala volumes in schizophrenia and other psychoses in the Northern Finland 1966 birth cohort, Schizophrenia Research, vol.75, issue.2-3, pp.283-294, 2005.
DOI : 10.1016/j.schres.2004.09.022

K. Tibell, H. Spies, and M. Borga, Fast Prototype Based Noise Reduction, Proceedings of the 16th Scandinavian Conference on Image Analysis, pp.159-168, 2009.
DOI : 10.1016/j.media.2008.02.004

F. Van-der-lijn, T. Den-heijer, M. M. Breteler, and W. J. Niessen, Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts, NeuroImage, vol.43, issue.4, pp.708-720, 2008.
DOI : 10.1016/j.neuroimage.2008.07.058

E. M. Van-rikxoort, I. Isgum, Y. Arzhaeva, M. Staring, S. Klein et al., Adaptive local multi-atlas segmentation: Application to the heart and the caudate nucleus, Medical Image Analysis, vol.14, issue.1, pp.39-49, 2010.
DOI : 10.1016/j.media.2009.10.001

D. Wang and D. M. Doddrell, A segmentation-based and partial-volume-compensated method for an accurate measurement of lateral ventricular volumes on T1-weighted magnetic resonance images, Magnetic Resonance Imaging, vol.19, issue.2, pp.267-273, 2001.
DOI : 10.1016/S0730-725X(01)00235-1

Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, Image Quality Assessment: From Error Visibility to Structural Similarity, IEEE Transactions on Image Processing, vol.13, issue.4, pp.600-612, 2004.
DOI : 10.1109/TIP.2003.819861

N. Wiest-daessle, S. Prima, P. Coupe, S. P. Morrissey, and C. Barillot, Rician Noise Removal by Non-Local Means Filtering for Low Signal-to-Noise Ratio MRI: Applications to DT-MRI, Med Image Comput Comput Assist Interv, vol.11, pp.171-179, 2008.
DOI : 10.1007/978-3-540-85990-1_21

URL : https://hal.archives-ouvertes.fr/inserm-00332388

J. Zhou and J. C. Rajapakse, Segmentation of subcortical brain structures using fuzzy templates, NeuroImage, vol.28, issue.4, pp.915-924, 2005.
DOI : 10.1016/j.neuroimage.2005.06.037

A. P. Zijdenbos, B. M. Dawant, R. A. Margolin, and A. C. Palmer, Morphometric analysis of white matter lesions in MR images: method and validation, IEEE Transactions on Medical Imaging, vol.13, issue.4, pp.716-724, 1994.
DOI : 10.1109/42.363096