Instance segmentation of upper aerodigestive tract cancer: site-specific outcomes

OBJECTIVE: To achieve instance segmentation of upper aerodigestive tract (UADT) neoplasms using a deep learning (DL) algorithm, and to identify differences in its diagnostic performance in three different sites: larynx/hypopharynx, oral cavity and oropharynx. METHODS: A total of 1034 endoscopic imag...

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Detalles Bibliográficos
Autores principales: Paderno, Alberto, Villani, Francesca Pia, Fior, Milena, Berretti, Giulia, Gennarini, Francesca, Zigliani, Gabriele, Ulaj, Emanuela, Montenegro, Claudia, Sordi, Alessandra, Sampieri, Claudio, Peretti, Giorgio, Moccia, Sara, Piazza, Cesare
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Pacini Editore Srl 2023
Materias:
Clinical Techniques and Technologies
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10366566/
https://www.ncbi.nlm.nih.gov/pubmed/37488992
http://dx.doi.org/10.14639/0392-100X-N2336

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10366566/
https://www.ncbi.nlm.nih.gov/pubmed/37488992
http://dx.doi.org/10.14639/0392-100X-N2336

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