RCFLA-YOLO: a deep learning-driven framework for the automated assessment of root canal filling quality in periapical radiographs

A performance comparison with similar studies in the literature indicates that the proposed method is among the top-performing approaches based on the applied evaluation metrics. Furthermore, this study has the potential to be one of the first to assess RCF quality in student procedures. In conclusion, the proposed method, with its notable strong performance, demonstrates its potential as an effective tool for developing decision support systems aimed at the automatic evaluation of RCF quality in preclinical dental education.