Computer-aided design and 3-dimensional artificial/convolutional neural network for digital partial dental crown synthesis and validation.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
28 01 2023
28 01 2023
Historique:
received:
24
10
2022
accepted:
18
01
2023
entrez:
28
1
2023
pubmed:
29
1
2023
medline:
1
2
2023
Statut:
epublish
Résumé
The current multiphase, invitro study developed and validated a 3-dimensional convolutional neural network (3D-CNN) to generate partial dental crowns (PDC) for use in restorative dentistry. The effectiveness of desktop laser and intraoral scanners in generating data for the purpose of 3D-CNN was first evaluated (phase 1). There were no significant differences in surface area [t-stat(df) = - 0.01 (10), mean difference = - 0.058, P > 0.99] and volume [t-stat(df) = 0.357(10)]. However, the intraoral scans were chosen for phase 2 as they produced a greater level of volumetric details (343.83 ± 43.52 mm
Identifiants
pubmed: 36709380
doi: 10.1038/s41598-023-28442-1
pii: 10.1038/s41598-023-28442-1
pmc: PMC9884213
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1561Informations de copyright
© 2023. The Author(s).
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