<![CDATA[The rapid advancement of digital technologies has significantly influenced the field of medical imaging, particularly through the integration of Artificial Intelligence (AI) and Augmented Reality (AR). These technologies offer transformative potential in improving diagnostic accuracy, enhancing surgical planning, and addressing the limitations of traditional radiological methods. This study aims to evaluate the roles and effectiveness of AI and AR in radiology by analyzing their applications in medical diagnosis and surgical visualization, with a focus on increasing diagnostic speed, precision, and accessibility, especially in resource-limited settings. A systematic literature review was conducted by examining 45 peer-reviewed articles published between 2017 and 2025, selected based on relevance, innovation, and applicability. Thematic analysis revealed that AI—especially models using convolutional neural networks—has demonstrated high accuracy in detecting lung disease, breast cancer, and brain tumors. Meanwhile, AR has shown potential in enhancing spatial understanding and accuracy in surgical procedures. Despite these benefits, several challenges were identified, including integration difficulties with existing hospital systems, algorithmic bias, regulatory constraints, and high costs. In conclusion, the integration of AI and AR represents a promising direction for the future of radiology. However, further research is needed to develop cost-effective systems, ensure ethical and inclusive AI training, and establish standardized protocols for implementation. This study provides a foundational overview for healthcare stakeholders aiming to adopt these technologies in pursuit of more equitable and efficient medical imaging practices.]]>
