Enhancing Caries Detection in Bitewing Radiographs Using YOLOv7.
Bitewing radiograph
Caries detection
Confidence threshold
Dental caries
Detection area
Journal
Journal of digital imaging
ISSN: 1618-727X
Titre abrégé: J Digit Imaging
Pays: United States
ID NLM: 9100529
Informations de publication
Date de publication:
12 2023
12 2023
Historique:
received:
02
03
2023
accepted:
09
06
2023
revised:
09
06
2023
pmc-release:
01
12
2024
medline:
23
10
2023
pubmed:
29
8
2023
entrez:
28
8
2023
Statut:
ppublish
Résumé
The study aimed to evaluate the impact of image size, area of detection (IoU) thresholds and confidence thresholds on the performance of the YOLO models in the detection of dental caries in bitewing radiographs. A total of 2575 bitewing radiographs were annotated with seven classes according to the ICCMS
Identifiants
pubmed: 37640971
doi: 10.1007/s10278-023-00871-4
pii: 10.1007/s10278-023-00871-4
pmc: PMC10584768
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2635-2647Informations de copyright
© 2023. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.
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