Real time Tooth caries and cavity detection using Convolutional Neural network

Real-time tooth caries and cavity detection using Convolutional Neural Networks (CNNs) represents a significant advancement in dental diagnostics. By leveraging deep learning algorithms, CNNs can analyze dental images, such as radiographs or intraoral photos, to identify signs of caries and cavities with high accuracy. The process typically involves training the CNN on a diverse dataset of labeled dental images, allowing the model to learn intricate patterns and features associated with dental decay. Once trained, the CNN can process new images in real-time, providing instant feedback to dental professionals. This technology not only enhances the diagnostic capabilities of dentists but also facilitates earlier intervention, potentially reducing the severity of dental issues and improving patient outcomes. The integration of CNNs into dental practice represents a promising step toward more efficient and effective oral healthcare.