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Corresponding Author

Mohammed M. Elmogy

Article Type

Review

Abstract

In dentistry, many diseases, such as gum, cavities, and oral cancer, affect people of all ages. Early treatment and diagnosis are crucial for minimizing dental diseases' effect on overall health and saving money in the long run. Traditional dental diagnosis methods, such as manual probing and visual inspection, are time-consuming and can be subject to human errors. Hence, a computer-aided diagnosis system based on computer vision and artificial intelligence (AI) techniques is needed. The considerable progress in computer vision and AI techniques offers many possibilities in dental diagnosis based on dental X-ray imaging modalities. Dental X-rays are used to diagnose diseases affecting the bones and the teeth. This survey provides a thorough analysis of current AI research, paving the way for advancements in the detection and classification of dental diseases. We analyze the different phases of a dental disease diagnosis system, explore the complexities of dental imaging modalities, and carefully assess benchmark datasets. In addition, we shed light on the assessment metrics used and highlight the critical problems that need to be solved in this field. Compiling this body of knowledge gives researchers a head start on their next projects and opens the door to developments in AI-powered dental diagnostics.

Keywords

Dentistry, Dental diseases, Dental X-ray, Deep learning, Features extraction

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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