Background <p>Alzheimer’s disease (AD) is one of the most prevalent neurodegenerative disorders worldwide and presents substantial challenges for early diagnosis, disease monitoring, and therapeutic evaluation. Neuroimaging techniques have become essential tools for visualizing structural and molecular alterations associated with AD; however, conventional imaging approaches are often limited by high cost, restricted accessibility, and limited specificity.</p> Objective <p>This review aims to critically evaluate current and emerging neuroimaging modalities in AD and to assess their potential for improving diagnostic accuracy, disease monitoring, and clinical decision-making.</p> Methods <p>A comprehensive review of published literature was conducted to examine the diagnostic utility, advantages, and limitations of established and advanced neuroimaging techniques used in AD research and clinical practice. Particular emphasis was placed on conventional modalities such as positron emission tomography (PET) and magnetic resonance imaging (MRI), as well as emerging technologies including second-generation tau-PET tracers, multimodal MRI strategies, and artificial intelligence (AI)-based analytical models.</p> Results <p>Traditional imaging modalities provide valuable insights into amyloid deposition, tau pathology, and structural brain changes associated with AD, but are constrained by limitations related to cost and specificity. Recent advances, including second-generation tau-PET tracers, multimodal MRI approaches integrating structural and functional data, and AI-driven predictive models, demonstrate improved diagnostic sensitivity and the potential for earlier disease detection.</p> Conclusion <p>The integration of advanced neuroimaging technologies with data-driven analytical frameworks offers significant potential for enhancing diagnostic precision and facilitating personalized approaches to AD management.</p> Graphical Abstract <p></p>