Identification Of Dental Implant Systems From Low-quality And Distorted Dental Radiographs Using Ai Trained On A Large Multi-center Dataset

This article discusses the importance of high-quality images in training deep learning algorithms for AI-driven visual recognition, specifically in the field of dental radiographs. The research aims to evaluate a state-of-the-art AI model trained on a large and diverse dataset to accurately identify different types of dental implant systems in low-quality and distorted radiographs. The study has the potential to improve diagnostic accuracy and patient outcomes in dental diagnostics.