Classification of Dental Radiographs Using Deep Learning

Objectives: To retrospectively assess radiographic data and to prospectively classify radiographs (namely, panoramic, bitewing, periapical, and cephalometric images), we compared three deep learning architectures for their classification performance. Methods: Our dataset consisted of 31,288 panorami...

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Detalles Bibliográficos
Autores principales: Cejudo, Jose E., Chaurasia, Akhilanand, Feldberg, Ben, Krois, Joachim, Schwendicke, Falk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8038360/
https://www.ncbi.nlm.nih.gov/pubmed/33916800
http://dx.doi.org/10.3390/jcm10071496

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8038360/
https://www.ncbi.nlm.nih.gov/pubmed/33916800
http://dx.doi.org/10.3390/jcm10071496

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