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Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
Published on: February 23, 2024
Artificial intelligence in dental radiology: a narrative review
Muneeba Ali1, Memoona Irfan1, Tooba Ali2
1Karachi Medical and Dental College, Karachi, Pakistan.
Abstract:
This article examines how artificial intelligence (AI) is revolutionizing dental radiology, a vital aspect of dental diagnosis and treatment planning. AI improves diagnosis accuracy through sophisticated applications like automated anomaly identification, image segmentation, and treatment planning, whereas traditional imaging techniques like periapical and panoramic radiography have limits. Clinical procedures are streamlined, and accurate dental condition diagnosis is made possible by methods such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs). AI contributes to improved patient outcomes by lowering radiation exposure and improving picture quality. Dental radiography has a bright future despite current obstacles including data collection and algorithm training; nonetheless, further study and cooperation are required to maximize AI's incorporation into clinical practice. AI has the potential to revolutionize dental diagnostics, despite obstacles in data collection and the requirement for strong algorithm training. The creation of innovative imaging modalities, further research on AI applications, and cooperative efforts between scientists, physicians, and industry participants are some of the future directions. The dentistry community may better utilize AI to enhance patient care and diagnostic skills by creating clear criteria for its integration. In the long run, AI has the potential to transform dental radiology, resulting in better treatment outcomes and a more effective practice.

