Artificial Intelligence for real-time identification and segmentation of root canal morphology using digital imaging

Proper recognition along with segmentation of root canal anatomies stands essential for successful endodontic procedures. Medical imaging approaches presently rely on human-assisted interpretation because these techniques perform slowly while showing potential errors. The research investigates the utilization of AI technology for automatic identification and segmentation of root canal shapes through digital image processing. A deep learning system uses CNN which train on annotated dental images to create its operation. Performance evaluation of the methodology relies on three parameters: accuracy, Dice coefficient and processing time. The test outcomes prove that the AI model which uses deep learning achieves better accuracy as well as time savings while segmenting root canal morphology.