F. Acar, J. P. Miller, M. C. Berk, G. Anderson, and K. J. Burchiel, Safety of Anterior Commissure-Posterior Commissure-Based Target Calculation of the Subthalamic Nucleus in Functional Stereotactic Procedures, Stereotactic and Functional Neurosurgery, vol.85, issue.6, pp.287-91, 2007.
DOI : 10.1159/000107361

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.726-764, 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.1266-77, 2009.
DOI : 10.1109/TMI.2009.2014372

K. Ashkan, P. Blomstedt, L. Zrinzo, S. Tisch, T. Yousry et al., Variability of the subthalamic nucleus: The case for direct MRI guided targeting, British Journal of Neurosurgery, vol.17, issue.3, pp.197-200, 2007.
DOI : 10.1080/02688690701272240

B. B. Avants, C. L. Epstein, M. Grossman, and J. C. Gee, Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain, Medical Image Analysis, vol.12, issue.1, pp.26-41, 2008.
DOI : 10.1016/j.media.2007.06.004

E. J. Brunenberg, B. Platel, P. A. Hofman, B. M. Ter-haar-romeny, and V. Visser-vandewalle, Magnetic resonance imaging techniques for visualization of the subthalamic nucleus, Journal of Neurosurgery, vol.115, issue.5, pp.971-84, 2011.
DOI : 10.3171/2011.6.JNS101571

A. Bubnov, [Neurosurgical anatomy of the zona incerta applicable to subthalamotomy], Vopr Neirokhir, issue.1, pp.36-40, 1975.

R. Camicioli, M. M. Moore, A. Kinney, E. Corbridge, K. Glassberg et al., Parkinson's disease is associated with hippocampal atrophy, Movement Disorders, vol.57, issue.7, pp.784-790, 2003.
DOI : 10.1002/mds.10444

Z. Caramanos, V. S. Fonov, S. J. Francis, S. Narayanan, G. B. Pike et al., Gradient distortions in MRI: Characterizing and correcting for their effects on SIENA-generated measures of brain volume change, NeuroImage, vol.49, issue.2, pp.1601-1612, 2010.
DOI : 10.1016/j.neuroimage.2009.08.008

F. Castro, C. Pollo, R. Meuli, P. Maeder, O. Cuisenaire et al., A Cross Validation Study of Deep Brain Stimulation Targeting: From Experts to Atlas-Based, Segmentation-Based and Automatic Registration Algorithms, IEEE Transactions on Medical Imaging, vol.25, issue.11, pp.1440-50, 2006.
DOI : 10.1109/TMI.2006.882129

A. Chen, K. J. Niermann, M. A. Deeley, and B. M. Dawant, Evaluation of multiple-atlas-based strategies for segmentation of the thyroid gland in head and neck CT images for IMRT, Physics in Medicine and Biology, vol.57, issue.1, pp.93-111, 2012.
DOI : 10.1088/0031-9155/57/1/93

D. L. Collins, P. Neelin, T. M. Peters, and A. C. Evans, Automatic 3D Intersubject Registration of MR Volumetric Data in Standardized Talairach Space, Journal of Computer Assisted Tomography, vol.18, issue.2, pp.192-205, 1994.
DOI : 10.1097/00004728-199403000-00005

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, 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.940-54, 2011.
DOI : 10.1016/j.neuroimage.2010.09.018

URL : https://hal.archives-ouvertes.fr/inserm-00541534

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.425-466, 2008.
DOI : 10.1109/TMI.2007.906087

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

S. Daniluk, K. , G. D. Ellias, S. A. Novak, P. Nazzaro et al., Assessment of the variability in the anatomical position and size of the subthalamic nucleus among patients with advanced Parkinson???s disease using magnetic resonance imaging, Acta Neurochirurgica, vol.47, issue.2, pp.201-211, 2010.
DOI : 10.1007/s00701-009-0514-z

W. Den-dunnen and M. Staal, Anatomical alterations of the subthalamic nucleus in relation to age: A postmortem study, Movement Disorders, vol.354, issue.7, pp.893-901, 2005.
DOI : 10.1002/mds.20417

V. Fonov, A. C. Evans, K. Botteron, C. R. Almli, R. C. Mckinstry et al., Unbiased average age-appropriate atlases for pediatric studies, NeuroImage, vol.54, issue.1, pp.313-340, 2011.
DOI : 10.1016/j.neuroimage.2010.07.033

B. Forstmann, M. Keuken, S. Jahfari, P. Bazin, J. Neumann et al., Cortico-subthalamic white matter tract strength predicts interindividual efficacy in stopping a motor response, NeuroImage, vol.60, issue.1, pp.370-375, 2012.
DOI : 10.1016/j.neuroimage.2011.12.044

D. Guehl, R. Edwards, E. Cuny, P. Burbaud, A. Rougier et al., Statistical determination of the optimal subthalamic nucleus stimulation site in patients with Parkinson disease, Journal of Neurosurgery, vol.106, issue.1, pp.101-111, 2007.
DOI : 10.3171/jns.2007.106.1.101

C. Haegelen, P. Coupe, V. Fonov, N. Guizard, P. Jannin et al., Automated segmentation of basal ganglia and deep brain structures in MRI of Parkinson???s disease, International Journal of Computer Assisted Radiology and Surgery, vol.26, issue.4, 2012.
DOI : 10.1007/s11548-012-0675-8

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.115-141, 2006.
DOI : 10.1016/j.neuroimage.2006.05.061

S. Hu, J. C. Pruessner, P. Coupe, and D. L. Collins, Volumetric analysis of medial temporal lobe structures in brain development from childhood to adolescence, NeuroImage, vol.74, pp.276-87, 2013.
DOI : 10.1016/j.neuroimage.2013.02.032

URL : https://hal.archives-ouvertes.fr/hal-00804345

M. Hutchinson and U. Raff, Structural changes of the substantia nigra in Parkinson's disease as revealed by MR imaging, Am J Neuroradiol, vol.21, pp.697-701, 2000.

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, 2009.
DOI : 10.1109/TMI.2008.2011480

M. Keuken, P. Bazin, A. Schafer, J. Neumann, R. Turner et al., Ultra-High 7T MRI of Structural Age-Related Changes of the Subthalamic Nucleus, Journal of Neuroscience, vol.33, issue.11, pp.4896-900, 2013.
DOI : 10.1523/JNEUROSCI.3241-12.2013

M. Kitajima, Y. Korogi, S. Kakeda, J. Moriya, N. Ohnari et al., Human subthalamic nucleus: evaluation with high-resolution MR imaging at 3.0??T, Neuroradiology, vol.216, issue.8, pp.675-81, 2008.
DOI : 10.1007/s00234-008-0388-4

G. Kleiner-fisman, D. N. Fisman, E. Sime, J. A. Saint-cyr, A. M. Lozano et al., Long-term follow up of bilateral deep brain stimulation of the subthalamic nucleus in patients with advanced Parkinson disease, Journal of Neurosurgery, vol.99, issue.3, pp.489-95, 2003.
DOI : 10.3171/jns.2003.99.3.0489

M. M. Lanotte, M. Rizzone, B. Bergamasco, G. Faccani, A. Melcarne et al., Deep brain stimulation of the subthalamic nucleus: anatomical, neurophysiological, and outcome correlations with the effects of stimulation, Journal of Neurology, Neurosurgery & Psychiatry, vol.72, issue.1, pp.53-61, 2002.
DOI : 10.1136/jnnp.72.1.53

L. Massey, M. Miranda, L. Zrinzo, O. Helli, H. Parkes et al., High resolution MR anatomy of the subthalamic nucleus: Imaging at 9.4T with histological validation, NeuroImage, vol.59, issue.3, pp.2035-2079, 2012.
DOI : 10.1016/j.neuroimage.2011.10.016

S. Mcclelland, B. Ford, P. B. Senatus, L. M. Winfield, Y. E. Du et al., Subthalamic stimulation for Parkinson disease: determination of electrode location necessary for clinical efficacy, Neurosurgical Focus, vol.19, issue.5, p.12, 2005.
DOI : 10.3171/foc.2005.19.5.13

E. B. Montgomery, Deep brain stimulation programming : principles and practice, 2010.
DOI : 10.1093/med/9780190259600.001.0001

J. H. Morra, Z. Tu, L. G. Apostolova, A. E. Green, C. Avedissian et al., Automated 3D mapping of hippocampal atrophy and its clinical correlates in 400 subjects with Alzheimer's disease, mild cognitive impairment, and elderly controls, Human Brain Mapping, vol.26, issue.Pt 2, pp.2766-88, 2009.
DOI : 10.1002/hbm.20708

D. G. Murphy, C. Decarli, M. B. Schapiro, S. I. Rapoport, and B. Horwitz, Age-Related Differences in Volumes of Subcortical Nuclei, Brain Matter, and Cerebrospinal Fluid in Healthy Men as Measured With Magnetic Resonance Imaging, Archives of Neurology, vol.49, issue.8, pp.839-845, 1992.
DOI : 10.1001/archneur.1992.00530320063013

A. Nagano-saito, Y. Washimi, Y. Arahata, T. Kachi, J. P. Lerch et al., Cerebral atrophy and its relation to cognitive impairment in Parkinson disease, Neurology, vol.64, issue.2, pp.224-229, 2005.
DOI : 10.1212/01.WNL.0000149510.41793.50

W. L. Nowinski, D. Belov, P. Pollak, and A. L. Benabid, A Probabilistic Functional Atlas ofthe Human Subthalamic Nucleus, Neuroinformatics, vol.2, issue.4, pp.381-98, 2004.
DOI : 10.1385/NI:2:4:381

O. 'gorman, R. L. Shmueli, K. Ashkan, K. Samuel, M. Lythgoe et al., Optimal MRI methods for direct stereotactic targeting of the subthalamic nucleus and globus pallidus, Eur Radiol, vol.21, pp.130-136, 2011.

S. Osher and J. A. Sethian, Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations, Journal of Computational Physics, vol.79, issue.1, pp.12-49, 1988.
DOI : 10.1016/0021-9991(88)90002-2

N. K. Patel, S. Khan, and S. S. Gill, Comparison of Atlas- and Magnetic-Resonance-Imaging-Based Stereotactic Targeting of the Subthalamic Nucleus in the Surgical Treatment of Parkinson’s Disease, Stereotactic and Functional Neurosurgery, vol.86, issue.3, pp.153-61, 2008.
DOI : 10.1159/000120427

E. O. Richter, T. Hoque, W. Halliday, A. M. Lozano, and J. A. Saint-cyr, Determining the position and size of the subthalamic nucleus based on magnetic resonance imaging results in patients with advanced Parkinson disease, Journal of Neurosurgery, vol.100, issue.3, pp.541-547, 2004.
DOI : 10.3171/jns.2004.100.3.0541

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.1428-1470, 2004.
DOI : 10.1016/j.neuroimage.2003.11.010

T. Rohlfing, C. R. Maurer, and . Jr, Shape-Based Averaging, IEEE Transactions on Image Processing, vol.16, issue.1, pp.153-61, 2007.
DOI : 10.1109/TIP.2006.884936

R. I. Scahill, C. Frost, R. Jenkins, J. L. Whitwell, M. N. Rossor et al., A Longitudinal Study of Brain Volume Changes in Normal Aging Using Serial Registered Magnetic Resonance Imaging, Archives of Neurology, vol.60, issue.7, 2003.
DOI : 10.1001/archneur.60.7.989

G. Schaltenbrand and W. Wahren, Atlas for stereotaxy of the human brain. Chicago. Year Book Medical Publishers, 1977.

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

C. Studholme, D. L. Hill, and D. J. Hawkes, An overlap invariant entropy measure of 3D medical image alignment, Pattern Recognition, vol.32, issue.1, pp.71-86, 1999.
DOI : 10.1016/S0031-3203(98)00091-0

J. Talairach and P. Tournoux, Co-planar stereotaxic atlas of the human brain : 3-dimensional proportional system : an approach to cerebral imaging, 1988.

F. J. Vingerhoets, J. G. Villemure, P. Temperli, C. Pollo, E. Pralong et al., Subthalamic DBS replaces levodopa in Parkinson's disease: Two-year follow-up, Neurology, vol.58, issue.3, pp.396-401, 2002.
DOI : 10.1212/WNL.58.3.396

H. Wang, J. W. Suh, S. R. Das, J. Pluta, C. Craige et al., Groupwise Segmentation with Multi-atlas Joint Label Fusion, IEEE Trans Pattern Anal Mach Intell, vol.35, pp.611-623, 2013.
DOI : 10.1007/978-3-642-40811-3_89

H. Wang, J. W. Suh, J. Pluta, M. Altinay, and P. Yushkevich, Optimal Weights for Multi-atlas Label Fusion, Inf Process Med Imaging, vol.22, pp.73-84, 2011.
DOI : 10.1007/978-3-642-22092-0_7

S. K. Warfield, K. H. Zou, and W. M. Wells, Simultaneous Truth and Performance Level Estimation (STAPLE): An Algorithm for the Validation of Image Segmentation, IEEE Transactions on Medical Imaging, vol.23, issue.7, pp.903-924, 2004.
DOI : 10.1109/TMI.2004.828354

K. L. Weiss, H. Pan, J. Storrs, W. Strub, J. L. Weiss et al., Clinical brain MR imaging prescriptions in Talairach space: technologist-and computer-driven methods, AJNR Am J Neuroradiol, vol.24, pp.922-931, 2003.

Y. M. Xiao, S. Beriault, G. B. Pike, and D. L. Collins, Multicontrast multiecho FLASH MRI for targeting the subthalamic nucleus, Magnetic Resonance Imaging, vol.30, issue.5, pp.627-640, 2012.
DOI : 10.1016/j.mri.2012.02.006

X. L. Zhu, W. Hamel, B. Schrader, D. Weinert, J. Hedderich et al., Magnetic Resonance Imaging-Based Morphometry and Landmark Correlation of Basal Ganglia Nuclei, Acta Neurochirurgica, vol.144, issue.10, pp.959-69, 2002.
DOI : 10.1007/s00701-002-0982-x