Deep learning neural networks to differentiate Stafne’s bone cavity from pathological radiolucent lesions of the mandible in heterogeneous panoramic radiography

This study aimed to develop a high-performance deep learning algorithm to differentiate Stafne’s bone cavity (SBC) from cysts and tumors of the jaw based on images acquired from various panoramic radiographic systems. Data sets included 176 Stafne’s bone cavities and 282 odontogenic cysts and tumors...

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Detalles Bibliográficos
Autores principales: Lee, Ari, Kim, Min Su, Han, Sang-Sun, Park, PooGyeon, Lee, Chena, Yun, Jong Pil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8291753/
https://www.ncbi.nlm.nih.gov/pubmed/34283883
http://dx.doi.org/10.1371/journal.pone.0254997

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8291753/
https://www.ncbi.nlm.nih.gov/pubmed/34283883
http://dx.doi.org/10.1371/journal.pone.0254997

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