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Article Dans Une Revue International Journal of Environmental Research and Public Health Année : 2023

Artificial Intelligence as a Decision-Making Tool in Forensic Dentistry: A Pilot Study with I3M

Romain Bui
  • Fonction : Auteur
Régis Iozzino
  • Fonction : Auteur
Raphaël Richert
Loïc Boussel
Cheraz Tafrount
  • Fonction : Auteur
Maxime Ducret
  • Fonction : Auteur

Résumé

Expert determination of the third molar maturity index (I3M) constitutes one of the most common approaches for dental age estimation. This work aimed to investigate the technical feasibility of creating a decision-making tool based on I3M to support expert decision-making. Methods: The dataset consisted of 456 images from France and Uganda. Two deep learning approaches (Mask R-CNN, U-Net) were compared on mandibular radiographs, leading to a two-part instance segmentation (apical and coronal). Then, two topological data analysis approaches were compared on the inferred mask: one with a deep learning component (TDA-DL), one without (TDA). Regarding mask inference, U-Net had a better accuracy (mean intersection over union metric (mIoU)), 91.2% compared to 83.8% for Mask R-CNN. The combination of U-Net with TDA or TDA-DL to compute the I3M score revealed satisfying results in comparison with a dental forensic expert. The mean ± SD absolute error was 0.04 ± 0.03 for TDA, and 0.06 ± 0.04 for TDA-DL. The Pearson correlation coefficient of the I3M scores between the expert and a U-Net model was 0.93 when combined with TDA and 0.89 with TDA-DL. This pilot study illustrates the potential feasibility to automate an I3M solution combining a deep learning and a topological approach, with 95% accuracy in comparison with an expert.
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Dates et versions

hal-04152348 , version 1 (03-04-2024)

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Citer

Romain Bui, Régis Iozzino, Raphaël Richert, Pascal Roy, Loïc Boussel, et al.. Artificial Intelligence as a Decision-Making Tool in Forensic Dentistry: A Pilot Study with I3M. International Journal of Environmental Research and Public Health, 2023, 20 (5), pp.4620. ⟨10.3390/ijerph20054620⟩. ⟨hal-04152348⟩

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