Five simultaneous artificial intelligence data challenges on ultrasound, CT, and MRI

Autor: B. Bresson, N. Poussange, M. Majer, Marc Zins, D. Guenoun, Olivier Hauger, S. Si-Mohamed, D. Istrati, Théo Estienne, M. Azoulay, S. Molière, Nathalie Lassau, E. Jehanno, C. Balleyguier, Caroline Caramella, A. Bergère, M. Boisserie, J. Behr, F. Dubrulle, J.-F. Meder, François Cornelis, E. Poncelet, A. Paisant, Raphaëlle Renard-Penna, N. Peyron Faure, H. Cauliez, Caroline Malhaire, T. Caramella, A. Perrey, P. de Vomecourt, François Bidault, C. Bordonne, S. Montagne, Alain Luciani, S. Caius Giurca, G. Garcia, M. Faivre-Pierre, Nicolas Amoretti, F. Desmots, Anne Cotten, M. Abitbol, V. Herreros, Aurélie Jalaguier-Coudray, Olivier Rouvière, J.-F. Budzik, J. Cagnol, Laure Fournier, Valérie Juhan, M. Faruch, C. Cyteval, T. Jacques, J. Bocquet, R. Lotte, T. Willaume, J.-L. Drape, S. Brunelle, A. Blum, M. Garetier, L. Di Marco, F. Pigneur

Publikováno v: Diagnostic and Interventional Imaging
Diagnostic and Interventional Imaging, 2019, 100 (4), pp.199-209. ⟨10.1016/j.diii.2019.02.001⟩
Diagnostic and Interventional Imaging, Elsevier, 2019, 100 (4), pp.199-209. ⟨10.1016/j.diii.2019.02.001⟩

Summary Purpose The goal of this data challenge was to create a structured dynamic with the following objectives: (1) teach radiologists the new rules of General Data Protection Regulation (GDPR), while building a large multicentric prospective datab

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https://hal.science/hal-02528753