Current Methods in Medical Image Segmentation, Annual Review of Biomedical Engineering, vol.2, issue.1, pp.315-337, 2000. ,
DOI : 10.1146/annurev.bioeng.2.1.315
Medical Image Segmentation Using Genetic Algorithms, IEEE Transactions on Information Technology in Biomedicine, vol.13, issue.2, pp.166-173, 2009. ,
DOI : 10.1109/TITB.2008.2007301
Statistical shape models for 3D medical image segmentation: A review, Medical Image Analysis, vol.13, issue.4, pp.543-563, 2009. ,
DOI : 10.1016/j.media.2009.05.004
A review of segmentation methods in short axis cardiac MR images, Medical Image Analysis, vol.15, issue.2, pp.169-184, 2011. ,
DOI : 10.1016/j.media.2010.12.004
URL : https://hal.archives-ouvertes.fr/hal-00551034
A comparative study of deformable contour methods on medical image segmentation, Image and Vision Computing, vol.26, issue.2, pp.141-163, 2008. ,
DOI : 10.1016/j.imavis.2007.07.010
Topology adaptive deformable surfaces for medical image volume segmentation, IEEE Transactions on Medical Imaging, vol.18, issue.10, pp.840-850, 1999. ,
DOI : 10.1109/42.811261
How hippocampus and cortex contribute to recognition memory: Revisiting the complementary learning systems model, Hippocampus, vol.27, issue.11, pp.1217-1227, 2010. ,
DOI : 10.1002/hipo.20855
A cortical-hippocampal system for declarative memory, Nature Reviews Neuroscience, vol.1, issue.1, pp.41-50, 2000. ,
DOI : 10.1038/35036213
Conjunctive representations in learning and memory: Principles of cortical and hippocampal function., Psychological Review, vol.108, issue.2, pp.311-345, 2001. ,
DOI : 10.1037/0033-295X.108.2.311
Genomic Anatomy of the Hippocampus, Neuron, vol.60, issue.6, pp.1010-1021, 2008. ,
DOI : 10.1016/j.neuron.2008.12.008
A meta-analysis of hippocampal atrophy rates in Alzheimer's disease, Neurobiology of Aging, vol.30, issue.11, pp.1711-1723, 2009. ,
DOI : 10.1016/j.neurobiolaging.2008.01.010
Allen Reference Atlases, 2004. ,
The Allen Brain Atlas: 5 years and beyond, Nature Reviews Neuroscience, vol.8, issue.11, pp.821-828, 2009. ,
DOI : 10.1038/nrn2722
An anatomically comprehensive atlas of the adult human brain transcriptome, Nature, vol.4, issue.7416, pp.391-399, 2012. ,
DOI : 10.1038/nature11405
In situ hybridization: Methods and applications, Journal of Clinical Laboratory Analysis, vol.2, issue.1, pp.2-9, 1997. ,
DOI : 10.1002/(SICI)1098-2825(1997)11:1<2::AID-JCLA2>3.0.CO;2-F
Automatic Hippocampus Localization in Histological Images using Differential Evolution-Based Deformable Models Automatic Segmentation of Hippocampus in Histological Images of Mouse Brains using Deformable Models and Random Forest, Proc. on 25th International Symposium on Computer-Based Medical Systems (CBMS'12), pp.299-307, 2012. ,
The Use of Active Shape Models For Locating Structures in Medical Images, 1994. ,
Active Shape Models-Their Training and Application, Computer Vision and Image Understanding, vol.61, issue.1, pp.38-59, 1995. ,
DOI : 10.1006/cviu.1995.1004
URL : https://www.escholar.manchester.ac.uk/api/datastream?publicationPid=uk-ac-man-scw:1d1862&datastreamId=POST-PEER-REVIEW-PUBLISHERS.PDF
Differential Evolution: A Survey of the State-of-the-Art, IEEE Transactions on Evolutionary Computation, vol.15, issue.1, pp.4-31, 2011. ,
DOI : 10.1109/TEVC.2010.2059031
Random forests, Maching Learning, pp.5-32, 2001. ,
Soft thresholding for medical image segmentation, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, pp.4752-4755, 2010. ,
DOI : 10.1109/IEMBS.2010.5626376
A Threshold Selection Method from Gray-Level Histograms, IEEE Transactions on Systems, Man, and Cybernetics, vol.9, issue.1, pp.62-66, 1979. ,
DOI : 10.1109/TSMC.1979.4310076
Geodesic active contours, Proceedings of IEEE International Conference on Computer Vision, pp.61-79, 1995. ,
DOI : 10.1109/ICCV.1995.466871
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.21.2196
Active contours without edges, IEEE Transactions on Image Processing, vol.10, issue.2, pp.266-277, 2001. ,
DOI : 10.1109/83.902291
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.2.1828
Automated atlas-based segmentation of NISSL-stained mouse brain sections using supervised learning, Programming and Computing Software, pp.245-251, 2011. ,
DOI : 10.1134/S0361768811050045
PROPAGATING DISTRIBUTIONS FOR SEGMENTATION OF BRAIN ATLAS, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.1304-1307, 2007. ,
DOI : 10.1109/ISBI.2007.357099
Genetic snakes: active contour models by genetic algorithms, Genetic and Evolutionary Computation in Image Processing and Computer Vision, ser. EURASIP Book Series on SP & C, pp.177-194, 2007. ,
Medial-Based Deformable Models in Nonconvex Shape-Spaces for Medical Image Segmentation, IEEE Transactions on Medical Imaging, vol.31, issue.1, pp.33-50, 2012. ,
DOI : 10.1109/TMI.2011.2162528
A genetic algorithmbased level set curve evolution for prostate segmentation on pelvic ct and mri images, Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques. IGI Global, pp.127-149, 2010. ,
Topological active models optimization with differential evolution, Expert Systems with Applications, vol.39, issue.15, pp.12-165, 2012. ,
DOI : 10.1016/j.eswa.2012.04.087
Comparison and Evaluation of Segmentation Techniques for Subcortical Structures in Brain MRI, Proc. of MICCAI'08, pp.409-416, 2008. ,
DOI : 10.1007/978-3-540-85988-8_49
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.903-921, 2004. ,
DOI : 10.1109/TMI.2004.828354
A comparison of ground truth estimation methods, International Journal of Computer Assisted Radiology and Surgery, vol.23, issue.7, pp.295-305, 2010. ,
DOI : 10.1007/s11548-009-0401-3
An efficient local Chan???Vese model for image segmentation, Pattern Recognition, vol.43, issue.3, pp.603-618, 2010. ,
DOI : 10.1016/j.patcog.2009.08.002