Three artificial intelligence data challenges based on CT and MRI.

Date publication

mars 2020

Journal

Diagnostic and interventional imaging

Auteurs

Membres identifiés du Cancéropôle Est :
Pr OHANA Mickaël

Tous les auteurs :
Lassau N, Bousaid I, Chouzenoux E, Lamarque JP, Charmettant B, Azoulay M, Cotton F, Khalil A, Lucidarme O, Pigneur F, Benaceur Y, Sadate A, Lederlin M, Laurent F, Chassagnon G, Ernst O, Ferreti G, Diascorn Y, Brillet PY, Creze M, Cassagnes L, Caramella C, Loubet A, Dallongeville A, Abassebay N, Ohana M, Banaste N, Cadi M, Behr J, Boussel L, Fournier L, Zins M, Beregi JP, Luciani A, Cotten A, Meder JF

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/32245723

Résumé

The second edition of the artificial intelligence (AI) data challenge was organized by the French Society of Radiology with the aim to: (i), work on relevant public health issues; (ii), build large, multicentre, high quality databases; and (iii), include three-dimensional (3D) information and prognostic questions.

Mots clés

Artificial intelligence (AI), Computed tomography (CT), Deep learning, Machine learning, Magnetic resonance imaging (MRI)

Référence

Diagn Interv Imaging. 2020 Mar 31;: