Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/58074
Title: A YOLO-V5 approach for the evaluation of normal fillings and overhanging fillings: an artificial intelligence study
Authors: Akgül, N.
Yilmaz, C.
Bilgir, E.
Çelik, Ö.
Baydar, O.
Bayrakdar, İŞ.
Keywords: Algorithms
Artificial Intelligence
Dental Restoration, Permanent
Humans
Radiography, Panoramic
Reference Values
Reproducibility of Results
algorithm
artificial intelligence
dental restoration
human
panoramic radiography
procedures
reference value
reproducibility
Abstract: Dental fillings, frequently used in dentistry to address various dental tissue issues, may pose problems when not aligned with the anatomical contours and physiology of dental and periodontal tissues. Our study aims to detect the prevalence and distribution of normal and overhanging filling restorations using a deep CNN architecture trained through supervised learning, on panoramic radiography images. A total of 10480 fillings and 2491 overhanging fillings were labeled using CranioCatch software from 2473 and 1850 images, respectively. After the data obtaining phase, validation (80%), training 10%), and test-groups (10%) were formed from images for both labelling. The YOLOv5x architecture was used to develop the AI model. The model's performance was assessed through a confusion matrix and sensitivity, precision, and F1 score values of the model were calculated. For filling, sensitivity is 0.95, precision is 0.97, and F1 score is 0.96; for overhanging were determined to be 0.86, 0.89, and 0.87, respectively. The results demonstrate the capacity of the YOLOv5 algorithm to segment dental radiographs efficiently and accurately and demonstrate proficiency in detecting and distinguishing between normal and overhanging filling restorations.
URI: https://doi.org/10.1590/1807-3107bor-2024.vol38.0098
https://hdl.handle.net/11499/58074
ISSN: 1807-3107
Appears in Collections:Diş Hekimliği Fakültesi Koleksiyonu
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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