Automatized Detection and Categorization of Fissure Sealants from Intraoral Digital Photographs Using Artificial Intelligence

The aim of the present study was to investigate the diagnostic performance of a trained convolutional neural network (CNN) for detecting and categorizing fissure sealants from intraoral photographs using the expert standard as reference. An image set consisting of 2352 digital photographs from perma...

Descripción completa

Detalles Bibliográficos
Autores principales: Schlickenrieder, Anne, Meyer, Ole, Schönewolf, Jule, Engels, Paula, Hickel, Reinhard, Gruhn, Volker, Hesenius, Marc, Kühnisch, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8469974/
https://www.ncbi.nlm.nih.gov/pubmed/34573949
http://dx.doi.org/10.3390/diagnostics11091608

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8469974/
https://www.ncbi.nlm.nih.gov/pubmed/34573949
http://dx.doi.org/10.3390/diagnostics11091608

Ejemplares similares