Intelligent Imaging in Dentistry: The Biomedical Engineering Revolution in AI -Powered Dental Radiology

Artificial intelligence (AI) has emerged as a transformative force in the domain of biomedical engineering, particularly within dental radiology. By leveraging machine learning (ML) and deep learning (DL) algorithms, AI systems can perform intricate analyses of radiographic images, surpassing traditional diagnostic limitations. This article provides a comprehensive overview of AI applications in dental imaging, including caries detection, orthodontic planning, lesion identification, and the analysis of cone-beam computed tomography (CBCT) and panoramic radiographs. A detailed examination of prevalent AI models such as convolutional neural networks (CNNs), support vector machines (SVMs), and transformer-based architectures is presented, alongside common datasets and image preprocessing pipelines. Furthermore, real-world case studies and hypothetical performance data are employed to illustrate AI’s diagnostic efficacy. While promising, challenges such as data scarcity, regulatory constraints, and clinical integration persist. The future of dental radiology is poised to be reshaped by explainable AI (XAI), multimodal integration, and EHR-connected diagnostic tools. This article underscores the critical role of biomedical engineers in shaping ethical, scalable, and effective AI-driven diagnostic platforms for dental care.

کلیدواژه ها:

Dental radiology ، Biomedical engineering ، Deep learning ، Machine learning ، CBCT ، Caries detection ، Dental diagnostics