AI-Assisted Oral Imaging Diagnosis in Clinical Applications of Dentistry: A Review
Artificial intelligence (AI), particularly deep learning and convolutional neural networks (CNNs), is increasingly used in dental and maxillofacial imaging for classification, detection, segmentation, and quantitative assessment. Applications include dental caries, periodontal bone loss, jaw lesions, orthodontic measurements, and impacted-tooth localization. This narrative review emphasizes the technical foundations of AI-assisted oral imaging, including CNN architectures, preprocessing, annotation, augmentation, evaluation, and external validation, while summarizing representative clinical applications. Current studies report promising performance in selected tasks, but generalizability is constrained by heterogeneous datasets, imaging protocols, annotation standards, and limited multicenter validation. Clinical translation further requires explainability, workflow integration, regulatory oversight, and prospective evaluation.
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