Artificial intelligence solution to classify pulmonary nodules on CT

Autor: Nathalie Lassau, N. Abassebay, I. Hammouamri, A. Loubet, M. Deloche, J.-A. Broyelle, D. Blanc, J. Brehant, M. Fiammante, Mathieu Lederlin, Guillaume Chassagnon, Gilbert Ferretti, Mickaël Ohana, V. Racine, Yann Diascorn, François Laurent, Hugo Veyssière, Pierre-Yves Brillet, Xavier Durando, J. Behr, Antoine Khalil, E. Verdier, Imad Bousaid, Caroline Caramella, E. Sinitambirivoutin, T. Besson, P. Cuingnet, Alexandre Sadate, Lucie Cassagnes, Angeline Ginzac

Publikováno v: Diagnostic and Interventional Imaging
Diagnostic and Interventional Imaging, 2020, 101 (12), pp.803-810. ⟨10.1016/j.diii.2020.10.004⟩
Diagnostic and Interventional Imaging, Elsevier, 2020, 101 (12), pp.803-810. ⟨10.1016/j.diii.2020.10.004⟩

International audience; Purpose: 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 mm3 or not, using machine learning and deep learning techniques.Ma

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1662c4a225e9c5a2d52de82a1d98e497
https://hal.science/hal-03054987/file/S2211568420302497.pdf

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