NeuroLOG ANR-06-TLOG-024 Software technologies for integration of process and data in medical imaging http://neurolog.polytech.unice.fr Bernard Gibaud 1 , Gilles Kassel 2 , Michel Dojat 3 , Bénédicte Batrancourt 4 , Franck Michel 5 , Alban Gaignard 5 , Johan Montagnat 5 1 INSERM / INRIA / CNRS / Univ. Rennes 1, IRISA Unit VISAGES U746, Rennes, France 2 Univ. de Picardie Jules Verne, MIS, EA 4290, Amiens, France 3 INSERM U836 / Univ. J. Fourier, Institut des Neurosciences, Grenoble, France 4 INSERM / CNRS / Univ. Pierre et Marie Curie, CRICM, UMR_S975, Paris, France 5 CNRS / UNS, I3S lab, MODALIS team, Sophia Antipolis, France AMIA 2011, Washington DC Supported by NeuroLOG: sharing neuroimaging data using an ontology-based federated approach
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NeuroLOG ANR-06-TLOG-024
Software technologies for integration of process and data in medical imaging
http://neurolog.polytech.unice.fr
Bernard Gibaud1, Gilles Kassel2, Michel Dojat3, Bénédicte Batrancourt4, Franck Michel5, Alban Gaignard5, Johan Montagnat5
1 INSERM / INRIA / CNRS / Univ. Rennes 1, IRISA Unit VISAGES U746, Rennes, France
2 Univ. de Picardie Jules Verne, MIS, EA 4290, Amiens, France 3 INSERM U836 / Univ. J. Fourier, Institut des Neurosciences, Grenoble, France 4 INSERM / CNRS / Univ. Pierre et Marie Curie, CRICM, UMR_S975, Paris, France
NeuroLOG: sharing neuroimaging data using an ontology-based
federated approach
Software technologies for integration of process, data and knowledge in medical imaging
NeuroLOG ANR-06-TLOG-024
Collaborative neurosciences
• Major challenge for this century − Degenerative diseases − Population aging − Pathophysiology understanding − Development / validation of new drugs
• Need to foster collaborative research − Validation / comparison of methods − Multi-centric disease-targeting studies − Multi-centric cross-disease studies
⇒ Require the sharing of large amounts of resources
2 AMIA 2011, Washington
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Collaborative research in neuroimaging
• What resources ? – Image data and associated data (technical, clinical, etc.) – Image processing tools – Computing resources
a Come up with a global federated view that hides data distribution and heterogeneity from the end-user
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Software technologies for integration of process, data and knowledge in medical imaging
NeuroLOG ANR-06-TLOG-024
Ontology design
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Software technologies for integration of process, data and knowledge in medical imaging
NeuroLOG ANR-06-TLOG-024
Ontology: scope
To assemble a common application ontology to provide a uniform and consistent modelling of shared information, e.g. : − Images (Datasets) − Image acquisition and image processing (Dataset processings) − Context of acquisition and exploitation of the images (Studies,
Subjects, Examinations, Centers, etc.) − Results of other kinds of explorations (Subject data acquisition
Software technologies for integration of process, data and knowledge in medical imaging
NeuroLOG ANR-06-TLOG-024
Discussion
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Software technologies for integration of process, data and knowledge in medical imaging
NeuroLOG ANR-06-TLOG-024
Discussion: ontology
• Domains that could not be included − Ontology of Regions of Interest (image ROIs) − Ontology of anatomical structures
• Need of convergence with other ontologies, e.g. NIF − Need to map BFO-based ontologies with our DOLCE-
based ontologies
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Discussion: mediator
• Data federator (SAP): the pros − Standard interface (jdbc) − Fully dynamic queries − Performance − User interface to defined mappings
• Data federator (SAP): the cons − No automatic re-configuring in case of error − NOT opensource
• Alternative solutions − OGSA-DAI / OGSA-DQP (e.g. used in BIRN, @NeurIST) − Fully semantic integration framework
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Conclusion / Perspectives
• We have presented a system for sharing image data and associated metadata according an ontology-based federated approach - Most of our objectives (not all !) could be met - We are currently applying for a continuation of this work in focused
neuroimaging research applications • We remain convinced that our ontology-based approach
is a promising one – Intelligent data querying and mediation – Complementary to regular relational querying
• However, it raises the issue of the convergence with other ontologies developed elsewhere, e.g. – NIF* / BIRN** in the USA – @NeurIST in Europe
* Neuroscience Information Framework ** Biomedical Informatics Research Network
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Acknowledgements
• ANR, for its financial support • All the people having contributed to NeuroLOG, espec. − Farooq Ahmad − Christian Barillot − Pascal Girard − David Godard − Diane Lingrand − Grégoire Malandain − Mélanie Pélégrini-Issac − Xavier Pennec − Javier Rojas Balderrama − Bacem Wali
• And all our clinical partners, especially − Gilles Edan, Jean-Christophe Ferré and Jean François Lebas