A. D. Gilliam and S. T. Acton, Echocardiographic Simulation for Validation of Automated Segmentation Methods, 2007 IEEE International Conference on Image Processing, pp.529-532, 2007.
DOI : 10.1109/ICIP.2007.4379882

M. Prastawa, E. Bullitt, and G. Gerig, Simulation of brain tumors in MR images for evaluation of segmentation efficacy, Medical Image Analysis, vol.13, issue.2, pp.297-311, 2009.
DOI : 10.1016/j.media.2008.11.002

G. Wagenknecht, H. Kaiser, T. Obladen, O. Sabri, and U. Buell, <title>Simulation of 3D MRI brain images for quantitative evaluation of image segmentation algorithms</title>, Medical Imaging 2000: Image Processing, pp.1074-1085, 2000.
DOI : 10.1117/12.387612

T. Glatard, A. Marion, H. Benoit-cattin, S. Camarasu-pop, P. Clarysse et al., Multi-modality image simulation with the Virtual Imaging Platform: Illustration on cardiac echography and MRI, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), 2012.
DOI : 10.1109/ISBI.2012.6235493

URL : https://hal.archives-ouvertes.fr/hal-00830243

S. Tomei, A. Reilhac, D. Visvikis, N. Boussion, C. Odet et al., OncoPET_DB: A Freely Distributed Database of Realistic Simulated Whole Body 18F-FDG PET Images for Oncology, IEEE Transactions on Nuclear Science, vol.57, issue.1, pp.246-255, 2010.
DOI : 10.1109/TNS.2009.2034375

URL : https://hal.archives-ouvertes.fr/hal-00703700

A. Reilhac, G. Batan, C. Michel, C. Grova, J. Tohka et al., PET-SORTEO: validation and development of database of Simulated PET volumes, IEEE Transactions on Nuclear Science, vol.52, issue.5, pp.1321-1328, 2005.
DOI : 10.1109/TNS.2005.858242

I. Castiglioni, I. Buvat, G. Rizzo, M. Gilardi, J. Feuardent et al., A publicly accessible Monte Carlo database for validation purposes in emission tomography, European Journal of Nuclear Medicine and Molecular Imaging, vol.25, issue.7, pp.1234-1273, 2005.
DOI : 10.1007/s00259-005-1832-x

S. Stute, P. Tylski, N. Grotus, and I. Buvat, LuCaS: Efficient Monte Carlo simulations of highly realistic PET tumor images, 2008 IEEE Nuclear Science Symposium Conference Record, pp.4010-4022, 2008.
DOI : 10.1109/NSSMIC.2008.4774162

R. K. Kwan, A. C. Evans, and G. B. Pike, MRI simulation-based evaluation of image-processing and classification methods, IEEE Transactions on Medical Imaging, vol.18, issue.11, pp.1085-1097, 1999.
DOI : 10.1109/42.816072

A. Dikshit, D. Wu, C. Wu, and W. Zhao, An online interactive simulation system for medical imaging education, Computerized Medical Imaging and Graphics, vol.29, issue.6, pp.395-404, 2005.
DOI : 10.1016/j.compmedimag.2005.02.001

F. Beekman and M. Viergever, Fast SPECT simulation including object shape dependant scatter, IEEE TMI, vol.14, pp.271-282, 1995.
DOI : 10.1109/42.387709

D. Lazos, K. Bliznakova, Z. Kolitsi, and N. Pallikarakis, An integrated research tool for X-ray imaging simulation, Computer Methods and Programs in Biomedicine, vol.70, issue.3, pp.241-251, 2003.
DOI : 10.1016/S0169-2607(02)00015-9

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

D. E. Peplow and K. Verghese, Digital mammography image simulation using Monte Carlo, Medical Physics, vol.24, issue.3, pp.568-579, 2000.
DOI : 10.1118/1.598896

I. Drobnjak, D. Gavaghan, E. Sli, J. Pitt-francis, and M. Jenkinson, Development of a functional magnetic resonance imaging simulator for modeling realistic rigid-body motion artifacts, Magnetic Resonance in Medicine, vol.50, issue.2, pp.364-380, 2006.
DOI : 10.1002/mrm.20939

W. Wein, A. Khamene, D. Clevert, O. Kutter, and N. Navab, Simulation and Fully Automatic Multimodal Registration of Medical Ultrasound, MICCAI'07, pp.136-143, 2007.
DOI : 10.1007/978-3-540-75757-3_17

D. Aiger and D. Cohen-or, Real-Time Ultrasound Imaging Simulation, Real-Time Imaging, vol.4, issue.4, pp.263-274, 1998.
DOI : 10.1006/rtim.1997.0089

R. Shams, R. Hartley, and N. Navab, Real-Time Simulation of Medical Ultrasound from CT Images, MICCAI'08, pp.734-741, 2008.
DOI : 10.1007/978-3-540-85990-1_88

S. Jan, D. Benoit, E. Becheva, T. Carlier, F. Cassol et al., GATE V6: a major enhancement of the GATE simulation platform enabling modelling of CT and radiotherapy, Physics in Medicine and Biology, vol.56, issue.4, pp.881-901, 2011.
DOI : 10.1088/0031-9155/56/4/001

URL : https://hal.archives-ouvertes.fr/in2p3-00559709

G. R. Christie, P. M. Nielsen, S. A. Blackett, C. P. Bradley, and P. J. Hunter, FieldML: concepts and implementation, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol.61, issue.1895, pp.1869-1884, 2009.
DOI : 10.1098/rsta.2009.0025

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2665020

N. D. Smith, M. Vecchi, D. Mccormick, O. Nordsletten, A. Camara et al., euHeart: personalized and integrated cardiac care using patient-specific cardiovascular modelling, Interface Focus, vol.41, issue.10, pp.349-364, 2011.
DOI : 10.1016/j.jbiomech.2008.04.035

URL : https://hal.archives-ouvertes.fr/inria-00616189

C. Rosse and J. Mejino, The Foundational Model of Anatomy Ontology, Anatomy Ontologies for Bioinformatics, pp.59-117, 2008.
DOI : 10.1007/978-1-84628-885-2_4

P. Schofield, G. Gkoutos, M. Gruenberger, J. Sundberg, and J. Hancock, Phenotype ontologies for mouse and man: bridging the semantic gap, Disease models & mechanisms, pp.5-6, 2010.
DOI : 10.1242/dmm.002790

G. Gkoutos, E. Green, A. Mallon, J. Hancock, and D. Davidson, Using ontologies to describe mouse phenotypes, Genome Biology, vol.6, pp.1-10, 2005.
DOI : 10.1002/cfg.430

URL : http://doi.org/10.1002/cfg.430

C. Langlotz, RadLex: A New Method for Indexing Online Educational Materials, RadioGraphics, vol.26, issue.6, pp.1595-1597, 2006.
DOI : 10.1148/rg.266065168

C. Tobon-gomez, F. M. Sukno, B. H. Bijnens, M. Huguet, and A. F. Frangi, Realistic simulation of cardiac magnetic resonance studies modeling anatomical variability, trabeculae, and papillary muscles, Magnetic Resonance in Medicine, vol.22, issue.Suppl 1, pp.280-288, 2011.
DOI : 10.1002/mrm.22621

A. Lemaitre, P. Segars, S. Marache, A. Reilhac, M. Hatt et al., Incorporating Patient-Specific Variability in the Simulation of Realistic Whole-Body <formula formulatype="inline"><tex Notation="TeX">$^{18}{\hbox{F-FDG}}$</tex></formula> Distributions for Oncology Applications, Proceedings of the IEEE, vol.97, issue.12, pp.2026-2038, 2009.
DOI : 10.1109/JPROC.2009.2027925

O. Kutter, R. Shams, and N. Navab, Visualization and GPU-accelerated simulation of medical ultrasound from CT images, Computer Methods and Programs in Biomedicine, vol.94, issue.3, pp.250-266, 2009.
DOI : 10.1016/j.cmpb.2008.12.011

G. Frisoni, A. Redolfi, D. Manset, M. Rousseau, A. Toga et al., Virtual imaging laboratories for marker discovery in neurodegenerative diseases, Nature Reviews Neurology, vol.5, issue.8, pp.429-467, 2011.
DOI : 10.1038/nrneurol.2011.99

D. E. Rex, J. Q. Ma, and A. W. Toga, The LONI Pipeline Processing Environment, NeuroImage, vol.19, issue.3, pp.1033-1048, 2003.
DOI : 10.1016/S1053-8119(03)00185-X

J. Montagnat, A. Gaignard, D. Lingrand, J. Rojas-balderrama, P. Collet et al., NeuroLOG: a community-driven middleware design, pp.49-58, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00461611

S. Shahand, M. Santcroos, Y. Mohammed, V. Korkhov, A. C. Luyf et al., Front-ends to Biomedical Data Analysis on Grids, 2011.

]. R. Barbera, F. Brasileiro, R. Bruno, L. Ciuffo, and D. Scardaci, Supporting e-Science Applications on e-Infrastructures: Some Use Cases from Latin America, Grid Computing, pp.33-55, 2011.
DOI : 10.1007/978-0-85729-676-4_2

T. Gruber, Toward principles for the design of ontologies used for knowledge sharing?, International Journal of Human-Computer Studies, vol.43, issue.5-6, pp.907-928, 1995.
DOI : 10.1006/ijhc.1995.1081

L. Temal, M. Dojat, G. Kassel, and B. Gibaud, Towards an ontology for sharing medical images and regions of interest in neuroimaging, Journal of Biomedical Informatics, vol.41, issue.5, pp.766-778, 2008.
DOI : 10.1016/j.jbi.2008.03.002

URL : https://hal.archives-ouvertes.fr/inserm-00344293

C. Masolo, S. Borgo, A. Gangemi, N. Guarino, and A. Oltramari, WonderWeb Deliverable D18. The WonderWeb Library of Foundational Ontologies and the DOLCE ontology, 2003.

G. Forestier, A. Marion, H. Benoit-cattin, P. Clarysse, D. Friboulet et al., Sharing object models for multi-modality medical image simulation: A semantic approach, 2011 24th International Symposium on Computer-Based Medical Systems (CBMS), 2011.
DOI : 10.1109/CBMS.2011.5999167

A. Marion, G. Forestier, H. Benoit-cattin, S. Camarasu-pop, P. Clarysse et al., Multi-modality medical image simulation of biological models with the Virtual Imaging Platform (VIP), 2011 24th International Symposium on Computer-Based Medical Systems (CBMS), pp.1-6, 2011.
DOI : 10.1109/CBMS.2011.5999141

N. Cerezo and J. Montagnat, Scientific workflows reuse through conceptual workflows, WORKS'11, pp.12-18, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00677831

J. Montagnat, B. Isnard, T. Glatard, K. Maheshwari, and M. Blay-fornarino, A data-driven workflow language for grids based on array programming principles, Proceedings of the 4th Workshop on Workflows in Support of Large-Scale Science, WORKS '09, pp.1-10, 2009.
DOI : 10.1145/1645164.1645171

URL : https://hal.archives-ouvertes.fr/hal-00677806

H. Benoit-cattin, G. Collewet, B. Belaroussi, H. Saint-jalmes, and C. Odet, The SIMRI project: a versatile and interactive MRI simulator, Journal of Magnetic Resonance, vol.173, issue.1, pp.97-115, 2005.
DOI : 10.1016/j.jmr.2004.09.027

J. Jensen and N. B. Svendsen, Calculation of pressure fields from arbitrarily shaped, apodized, and excited ultrasound transducers, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, vol.39, issue.2, pp.262-267, 1992.
DOI : 10.1109/58.139123

J. Tabary, S. Marache, S. Valette, W. Segars, and C. Lartizien, Realistic X-ray CT simulation of the XCAT phantom with SINDBAD, 2009 IEEE Nuclear Science Symposium Conference Record (NSS/MIC), pp.3980-3983, 2009.
DOI : 10.1109/NSSMIC.2009.5401942

URL : https://hal.archives-ouvertes.fr/hal-00508844

A. Tsaregorodtsev, N. Brook, A. C. Ramo, P. Charpentier, J. Closier et al., DIRAC3 ??? the new generation of the LHCb grid software, Journal of Physics: Conference Series, p.62029, 2009.
DOI : 10.1088/1742-6596/219/6/062029

URL : https://hal.archives-ouvertes.fr/in2p3-00383712

R. Ferreira-da-silva, S. Camarasu-pop, B. Grenier, V. Hamar, D. Manset et al., Multi-Infrastructure Workflow Execution for Medical Simulation in the Virtual Imaging Platform, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00677827

L. Moreau, J. Freire, J. Futrelle, R. Mcgrath, J. Myers et al., The Open Provenance Model: An Overview, Provenance and Annotation of Data and Processes, pp.323-326, 2008.
DOI : 10.1007/978-3-540-89965-5_31

R. Haddad, Un modéle anthropomorphique et dynamique du thorax respirant et du coeur battant, 2007.

W. Segars, G. Sturgeon, S. Mendonca, J. Grimes, and B. M. Tsui, 4D XCAT phantom for multimodality imaging research, Medical Physics, vol.36, issue.12, pp.4902-4915, 2010.
DOI : 10.1118/1.3480985

S. Marache, R. Prost, J. M. Rouet, and C. Lartizien, Incorporating patient-specific variability in the OncoPET DB database, IEEE NSS- MIC, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00722960

A. J. Reader, S. Ally, F. Bakatselos, R. Manavaki, R. J. Walledge et al., One-pass list-mode EM algorithm for high-resolution 3-D PET image reconstruction into large arrays, IEEE Transactions on Nuclear Science, vol.49, issue.3, pp.693-699, 2002.
DOI : 10.1109/TNS.2002.1039550

P. Schmitt, M. A. Griswold, P. M. Jakob, M. Kotas, V. Gulani et al., Inversion recovery TrueFISP: Quantification ofT1,T2, and spin density, Magnetic Resonance in Medicine, vol.6, issue.4, pp.661-668, 2004.
DOI : 10.1002/mrm.20058

G. J. Stanisz, E. E. Odrobina, J. Pun, M. Escaravage, S. J. Graham et al., T1, T2 relaxation and magnetization transfer in tissue at 3T, Magnetic Resonance in Medicine, vol.21, issue.3, pp.507-519, 2005.
DOI : 10.1002/mrm.20605

E. R. Melhem, D. A. Israel, S. Eustace, and H. Jara, MR of the spine with a fast T1-weighted fluid-attenuated inversion recovery sequence, AJNR Am J Neuroradiol, vol.18, issue.3, pp.447-54, 1997.

M. Alessandrini, H. Liebgott, D. Friboulet, and O. Bernard, Highly realistic simulation of echocardiographic image sequences for groundtruth validation of motion estimation, IEEE ICIP'12