AI-based identification of dental implant manufacturers using periapical radiographs
1. Title:Automated Identification of Dental Implants Using Artificial Intelligence
2. Authors: Rafael Pereira da Mata Santos; Higor Eduardo Vieira Oliveira Prado; Idalísio Soares Aranha Neto; Guilherme Augusto Alves de Oliveira; Amaro Ilídio Vespasiano Silva; Elton Gonçalves Zenóbio; Flávio Ricardo Manzi
3. Summary: This study aims to develop and evaluate a computer-assisted system using convolutional neural networks (CNN) to identify dental implant manufacturers from digital periapical radiographs. Using a sample of 1,800 radiographs from three manufacturers (Straumann, Neodent, and SIN), the researchers trained a deep learning model that achieved a final validation accuracy of 85.29%. The findings suggest that this AI-driven approach provides a precise method for identifying implant brands, which is a common challenge in clinical prosthetic transitions and forensic identification when patient records are unavailable.
5.13. Project Objective: To develop and evaluate the accuracy of a computer-assisted system based on AI for detecting and identifying dental implant brands using digital periapical radiographs
6. Clinical Relevance: Identifying implant models is a significant challenge for dentists beginning the prosthetic phase of treatment or for forensic professionals when previous records are missing. Because there are numerous brands with different connection systems, clinical examination or standard radiographic analysis by humans is often insufficient and subject to interobserver variability. This AI system provides a precise, automated method that eliminates dependence on a dentist's individual expertise, thereby increasing agility and safety in clinical practice and supporting forensic human identification
