Deep Learning for the Automatic Quantification of Pleural Plaques in Asbestos-Exposed Subjects

Objective: This study aimed to develop and validate an automated artificial intelligence (AI)-driven quantification of pleural plaques in a population of retired workers previously occupationally exposed to asbestos. Methods: CT scans of former workers previously occupationally exposed to asbestos w...

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Detalles Bibliográficos
Autores principales: Benlala, Ilyes, De Senneville, Baudouin Denis, Dournes, Gael, Menant, Morgane, Gramond, Celine, Thaon, Isabelle, Clin, Bénédicte, Brochard, Patrick, Gislard, Antoine, Andujar, Pascal, Chammings, Soizick, Gallet, Justine, Lacourt, Aude, Delva, Fleur, Paris, Christophe, Ferretti, Gilbert, Pairon, Jean-Claude, Laurent, François
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8835296/
https://www.ncbi.nlm.nih.gov/pubmed/35162440
http://dx.doi.org/10.3390/ijerph19031417

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8835296/
https://www.ncbi.nlm.nih.gov/pubmed/35162440
http://dx.doi.org/10.3390/ijerph19031417

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