M. Tovi, MR imaging in cerebral gliomas analysis of tumour tissue components, Acta radiologica. Supplementum, vol.384, issue.1, 1993.

E. Bearer, J. Lowengrub, H. Frieboes, Y. Chuang, F. Jin et al., Multiparameter Computational Modeling of Tumor Invasion, Cancer Research, vol.69, issue.10, p.694493, 2009.
DOI : 10.1158/0008-5472.CAN-08-3834

H. Frieboes, J. Lowengrub, S. Wise, X. Zheng, P. Macklin et al., Computer simulation of glioma growth and morphology, NeuroImage, vol.37, pp.59-70, 2007.
DOI : 10.1016/j.neuroimage.2007.03.008

S. Sanga, H. Frieboes, X. Zheng, R. Gatenby, E. Bearer et al., Predictive oncology: A review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth, NeuroImage, vol.37, pp.120-134, 2007.
DOI : 10.1016/j.neuroimage.2007.05.043

C. Wang, J. Rockhill, M. Mrugala, D. Peacock, A. Lai et al., Prognostic Significance of Growth Kinetics in Newly Diagnosed Glioblastomas Revealed by Combining Serial Imaging with a Novel Biomathematical Model, Cancer Research, vol.69, issue.23, p.699133, 2009.
DOI : 10.1158/0008-5472.CAN-08-3863

J. D. Murray, Mathematical biology, 2002.

K. Swanson, E. Alvord, and J. Murray, A quantitative model for differential motility of gliomas in grey and white matter, Cell Proliferation, vol.29, issue.5, pp.317-330, 2000.
DOI : 10.1046/j.1365-2184.2000.00177.x

A. Giese, L. Kluwe, B. Laube, H. Meissner, M. Berens et al., Migration of Human Glioma Cells on Myelin, Neurosurgery, vol.38, issue.4, pp.755-764, 1996.
DOI : 10.1227/00006123-199604000-00026

S. Jbabdi, E. Mandonnet, H. Duffau, L. Capelle, K. Swanson et al., Simulation of anisotropic growth of low-grade gliomas using diffusion tensor imaging, Magnetic Resonance in Medicine, vol.6, issue.3, pp.616-624, 2005.
DOI : 10.1002/mrm.20625

O. Clatz, M. Sermesant, P. Bondiau, H. Delingette, S. K. Warfield et al., Realistic simulation of the 3-D growth of brain tumors in MR images coupling diffusion with biomechanical deformation, IEEE Transactions on Medical Imaging, vol.24, issue.10, pp.1334-1346, 2005.
DOI : 10.1109/TMI.2005.857217

E. 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

K. Swanson, C. Bridge, J. Murray, and E. Alvord, Virtual and real brain tumors: using mathematical modeling to quantify glioma growth and invasion, Journal of the Neurological Sciences, vol.216, issue.1, pp.1-10, 2003.
DOI : 10.1016/j.jns.2003.06.001

T. Colin, A. Iollo, and D. Lombardi, SYSTEM IDENTIFICATION IN TUMOR GROWTH MODELING USING SEMI-EMPIRICAL EIGENFUNCTIONS, Mathematical Models and Methods in Applied Sciences, vol.22, issue.06, p.1250003, 2012.
DOI : 10.1142/S0218202512500030

E. Konukoglu, M. Sermesant, O. Clatz, J. Peyrat, H. Delingette et al., A Recursive Anisotropic Fast Marching Approach to Reaction Diffusion Equation: Application to Tumor Growth Modeling, Proceedings of the 20th International Conference on Information Processing in Medical Imaging (IPMI'07), pp.686-699
DOI : 10.1007/978-3-540-73273-0_57

URL : https://hal.archives-ouvertes.fr/inria-00616056

E. Konukoglu, O. Clatz, P. Bondiau, M. Sermesant, H. Delingette et al., Towards an Identification of Tumor Growth Parameters from Time Series of Images, Medical Image Computing and Computer-Assisted Intervention, pp.549-556, 2007.
DOI : 10.1007/978-3-540-75757-3_67

URL : https://hal.archives-ouvertes.fr/inria-00616046

E. Konukoglu, O. Clatz, B. Menze, B. Stieltjes, M. Weber et al., Image Guided Personalization of Reaction-Diffusion Type Tumor Growth Models Using Modified Anisotropic Eikonal Equations, IEEE Transactions on Medical Imaging, vol.29, issue.1, pp.77-95, 2009.
DOI : 10.1109/TMI.2009.2026413

URL : https://hal.archives-ouvertes.fr/inria-00616100

L. M. Deangelis, Brain Tumors, New England Journal of Medicine, vol.344, issue.2, pp.114-123, 2001.
DOI : 10.1056/NEJM200101113440207

E. C. Kaal and C. J. Vecht, The management of brain edema in brain tumors, Current Opinion in Oncology, vol.16, issue.6, p.593, 2004.
DOI : 10.1097/01.cco.0000142076.52721.b3

I. Whittle, The dilemma of low grade glioma, Journal of Neurology, Neurosurgery & Psychiatry, vol.75, issue.suppl_2, pp.31-36, 2004.
DOI : 10.1136/jnnp.2004.040501

A. Gooya, G. Biros, and C. Davatzikos, Deformable Registration of Glioma Images Using EM Algorithm and Diffusion Reaction Modeling, IEEE Transactions on Medical Imaging, vol.30, issue.2, pp.375-390, 2011.
DOI : 10.1109/TMI.2010.2078833

A. Gooya, K. Pohl, M. Bilello, G. Biros, and C. Davatzikos, Joint Segmentation and Deformable Registration of Brain Scans Guided by a Tumor Growth Model, Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011, pp.532-540, 2011.
DOI : 10.1109/42.790458

A. Gooya, K. Pohl, M. Bilello, L. Cirillo, G. Biros et al., GLISTR: Glioma Image Segmentation and Registration, IEEE Transactions on Medical Imaging, vol.31, issue.10, pp.311941-1954, 2012.
DOI : 10.1109/TMI.2012.2210558

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4371551

F. Laigle-donadey, N. Martin-duverneuil, J. Lejeune, E. Criniere, L. Capelle et al., Correlations between molecular profile and radiologic pattern in oligodendroglial tumors, Neurology, vol.63, issue.12, p.632360, 2004.
DOI : 10.1212/01.WNL.0000148642.26985.68

S. Drabycz, G. Roldán, P. De-robles, D. Adler, J. Mcintyre et al., An analysis of image texture, tumor location, and MGMT promoter methylation in glioblastoma using magnetic resonance imaging, NeuroImage, vol.49, issue.2, pp.1398-1405, 2010.
DOI : 10.1016/j.neuroimage.2009.09.049

A. R. Anderson, A hybrid mathematical model of solid tumour invasion: the importance of cell adhesion, Mathematical Medicine and Biology, vol.22, issue.2, pp.163-186, 2005.
DOI : 10.1093/imammb/dqi005

A. Sottoriva, J. J. Verhoeff, T. Borovski, S. K. Mcweeney, L. Naumov et al., Cancer Stem Cell Tumor Model Reveals Invasive Morphology and Increased Phenotypical Heterogeneity, Cancer Research, vol.70, issue.1, p.46, 2010.
DOI : 10.1158/0008-5472.CAN-09-3663

A. Kansal, S. Torquato, E. Chiocca, and T. Deisboeck, Emergence of a Subpopulation in a Computational Model of Tumor Growth, Journal of Theoretical Biology, vol.207, issue.3, pp.431-441, 2000.
DOI : 10.1006/jtbi.2000.2186

G. S. Young, Advanced MRI of Adult Brain Tumors, Neurologic Clinics, vol.25, issue.4, pp.947-973, 2007.
DOI : 10.1016/j.ncl.2007.07.010

P. Tracqui, G. Cruywagen, D. Woodward, G. Bartoo, J. C. Murraye et al., A mathematical model of glioma growth: the effect of chemotherapy on spatio-temporal growth, Cell Proliferation, vol.32, issue.1, pp.17-31, 1995.
DOI : 10.1016/S0022-5193(87)80171-6

M. Powell, The bobyqa algorithm for bound constrained optimization without derivatives, 2009.

L. E. Bohman, K. R. Swanson, J. L. Moore, R. Rockne, C. Mandigo et al., Magnetic Resonance Imaging Characteristics of Glioblastoma Multiforme: Implications for Understanding Glioma Ontogeny, Neurosurgery, vol.67, issue.5, p.671319, 2010.
DOI : 10.1227/NEU.0b013e3181f556ab

E. Stretton, E. Mandonnet, E. Geremia, H. Bjoern, H. Menze et al., Predicting the Location of Glioma Recurrence after a Resection Surgery, Proceedings of 2nd International MICCAI Workshop on Spatiotemporal Image Analysis for Longitudinal and Time-Series Image Data (STIA'12), 2012.
DOI : 10.1007/978-3-642-33555-6_10

URL : https://hal.archives-ouvertes.fr/hal-00813870

E. Konukoglu, O. Clatz, P. Y. Bondiau, H. Delingette, and N. Ayache, Extrapolating glioma invasion margin in brain magnetic resonance images: Suggesting new irradiation margins, Medical Image Analysis, vol.14, issue.2, pp.111-125, 2010.
DOI : 10.1016/j.media.2009.11.005

URL : https://hal.archives-ouvertes.fr/inria-00616107

. Capelle, Continuous growth of mean tumor diameter in a subset of grade ii gliomas, Annals of neurology, vol.53, issue.4, pp.524-528, 2003.

H. Harpold, E. C. Alvord, and J. K. Swanson, The Evolution of Mathematical Modeling of Glioma Proliferation and Invasion, Journal of Neuropathology and Experimental Neurology, vol.66, issue.1, 2007.
DOI : 10.1097/nen.0b013e31802d9000