Elay Faraji Bashir - Sanjesh’e No high school, Tabriz, Iran
Masoumeh Pourzaresorkhi - Department of Computer Science, Science and research branch of Azad University, Tehran,Iran
Maedeh Abedini Bagha - Roshdiyeh Higher Education Institute, Tabriz, East Azerbaijan Province, Iran,
Mahsa Foroughi - Department of electrical engineering,Tafaresh University, Tafaresh city, Iran,

Tooth decay is a common problem in dental radiography that affects a significant part of oral diseases.Early detection and prevention of tooth decay are crucial for effective treatment. However, accuratelydiagnosing dental caries remains challenging and has gained attention in international oral research.Computer-aided detection of caries using X-ray images has emerged as a potential solution. Artificialintelligence, particularly deep learning, has aided dentists in detecting tooth decay in X-ray imageseffectively. This research investigates the use of deep learning architectures for diagnosis,classification, and segmentation of dental X-ray images. By leveraging these advanced techniques,dentists can improve their ability to detect and treat dental caries promptly and accurately. Inconclusion, the use of deep learning in dental radiography has shown promising results in accuratelydetecting and classifying dental caries from X-ray images. This technology has the potential torevolutionize the field of dentistry by improving the accuracy and efficiency of diagnosis and treatmentof tooth decay.

Deep learning, Dental caries, Diagnosis, X-ray images.