RT Journal Article
T1 Artificial Intelligence Techniques for Automatic Detection of Peri‑implant Marginal Bone Remodeling in Intraoral Radiographs
A1 Vera González, Vicente
A1 Besada Portas, Eva
A1 Pajares Martínsanz, Gonzalo
A1 Gómez Silva, María José
A1 Aliaga Vera, Ignacio Joaquín
A1 Pedrera Canal, María
A1 Vera, María
A1 López-González, Clara Isabel
A1 Gascó, Esther
AB Peri-implantitis can cause marginal bone remodeling around implants. The aim is to develop an automatic image processing approach based on two artificial intelligence (AI) techniques in intraoral (periapical and bitewing) radiographs to assistdentists in determining bone loss. The first is a deep learning (DL) object-detector (YOLOv3) to roughly identify (no exactlocalization is required) two objects: prosthesis (crown) and implant (screw). The second is an image understanding-based(IU) process to fine-tune lines on screw edges and to identify significant points (intensity bone changes, intersectionsbetween screw and crown). Distances between these points are used to compute bone loss. A total of 2920 radiographswere used for training (50%) and testing (50%) the DL process. The mAP@0.5 metric is used for performance evaluation ofDL considering periapical/bitewing and screws/crowns in upper and lower jaws, with scores ranging from 0.537 to 0.898(sufficient because DL only needs an approximation). The IU performance is assessed with 50% of the testing radiographsthrough the t test statistical method, obtaining p values of 0.0106 (line fitting) and 0.0213 (significant point detection). TheIU performance is satisfactory, as these values are in accordance with the statistical average/standard deviation in pixelsfor line fitting (2.75/1.01) and for significant point detection (2.63/1.28) according to the expert criteria of dentists, whoestablish the ground-truth lines and significant points. In conclusion, AI methods have good prospects for automatic boneloss detection in intraoral radiographs to assist dental specialists in diagnosing peri-implantitis.
PB Springer
YR 2023
FD 2023-07-01
LK https://hdl.handle.net/20.500.14352/87321
UL https://hdl.handle.net/20.500.14352/87321
LA eng
NO Vera, M., Gómez-Silva, M.J., Vera, V. et al. Artificial Intelligence Techniques for Automatic Detection of Peri-implant Marginal Bone Remodeling in Intraoral Radiographs. J Digit Imaging (2023). https://doi.org/10.1007/s10278-023-00880-3
DS Docta Complutense
RD 6 abr 2025