Revolutionizing Nano-Orthodontic Diagnosis and Treatment through AI-Enhanced CBCT Image Analysis: New Frontiers in Deep Learning
نویسندگان
1 UCLA School of Dentistry, University of California, Los Angeles, CA 90095, USA
2 Department of dentistry, Islamic Azad University of Tehran Medical Sciences, Tehran, Iran
3 School of Dentistry, Tehran University of Medical sciences, Tehran, Iran
4 Department of dentistry, Islamic Azad University of Tehran Medical Sciences, Tehran, Iran
5 Department of dentistry, Islamic Azad University of Tehran Medical Sciences, Tehran, Iran
6 The City of London Dental School, University of Greater Manchester, Bolton, UK
doi
10.22034/nmrj.2025.03.004چکیده
This review paper explores the transformative integration of artificial intelligence (AI) and nanotechnology in orthodontics, focusing on how AI-enhanced cone-beam computed tomography (CBCT) image analysis is revolutionizing diagnosis and treatment. The paper details advances in digital imaging, emphasizing the impact of deep learning algorithms, such as Convolutional Neural Networks and Vision Transformers, which automate image interpretation, improve diagnostic accuracy, and enable personalized treatment strategies. It also highlights the role of nanomaterials in improving orthodontic components through enhanced biocompatibility, antimicrobial protection, and smart functionalities. The convergence of AI and nanotechnology marks a paradigm shift in precision orthodontics, though challenges such as data privacy, algorithmic bias, and clinical integration remain. Addressing these challenges is essential to achieve safe, effective, and widely adopted deployment of these technologies in clinical practice.
