Applications of artificial intelligence in intraoral scanning to enhance

Introduction: The goal of this study is to determine the transformative effect of AI on IOS technology, the cornerstone of modern digital dentistry. An increasing need exists to improve the accuracy, efficiency, and diagnostic yield of ۳D data derived from IOS for prosthodontics, orthodontics, and implantology. Methods: This analysis proceeds with a structured synthesis of recent evidence from the scientific literature and a comparative evaluation of AI capabilities embedded within leading commercial IOS platforms. This will focus specifically on AI-driven functionalities for data acquisition, automated interpretation, and integration into digital workflows. Results: AI algorithms significantly improve the performance of IOS by ensuring real-time scan guidance, automated segmentation, and precise margin detection. Advanced capabilities include biogenetic restorative design and multimodal data fusion. Comparative analysis reveals their varied strategic implementations across leading platforms. Discussion: AI-augmented IOS enables a shift toward data-driven, personalized treatment planning. However, to reach clinical integration, challenges in data standardization, algorithm generalizability, and workflow interoperability under professional oversight would have to be tackled.

کلیدواژه ها:

Artificial Intelligence ، Intraoral Scanners ، Digital Dentistry ، Digital Workflows ، Image Segmentation ، Margin Line Detection ، Multimodal Data Fusion ، Personalized Treatment Planning