This book explores the evolution of dental imaging from conventional film-based radiography to modern digital imaging systems and the growing integration of artificial intelligence (AI) in dental diagnostics. It discusses the principles, techniques, advantages, and limitations of conventional and digital imaging modalities, including intraoral radiography, panoramic imaging, cephalometry, and CBCT. The review further highlights the fundamentals of AI, machine learning, deep learning, and convolutional neural networks in dental radiology. Special emphasis is placed on AI-assisted image interpretation, automated detection and segmentation, quantitative analysis, workflow integration with PACS, and the role of AI as a clinical decision-support tool. The dissertation aims to critically evaluate how AI enhances diagnostic accuracy, efficiency, and reproducibility in dental imaging while emphasizing the continued importance of clinician oversight and ethical implementation.
AmazonPagina's: 124, Paperback, LAP LAMBERT Academic Publishing
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