Artificial intelligence solution to classify pulmonary nodules on CT.
Fiche publication
Date publication
novembre 2020
Journal
Diagnostic and interventional imaging
Auteurs
Membres identifiés du Cancéropôle Est :
Pr OHANA Mickaël
Tous les auteurs :
Blanc D, Racine V, Khalil A, Deloche M, Broyelle JA, Hammouamri I, Sinitambirivoutin E, Fiammante M, Verdier E, Besson T, Sadate A, Lederlin M, Laurent F, Chassagnon G, Ferretti G, Diascorn Y, Brillet PY, Cassagnes L, Caramella C, Loubet A, Abassebay N, Cuingnet P, Ohana M, Behr J, Ginzac A, Veyssiere H, Durando X, Bousaïd I, Lassau N, Brehant J
Lien Pubmed
Résumé
The purpose of this study was to create an algorithm to detect and classify pulmonary nodules in two categories based on their volume greater than 100 mm or not, using machine learning and deep learning techniques.
Mots clés
Deep learning, Lung cancer, Machine learning., Pulmonary nodule, Support vector machine
Référence
Diagn Interv Imaging. 2020 Nov 6;: