AI-Enhanced Decision Support for Radiology Technicians

The exponential rise in diagnostic imaging demands has outpaced the capacity of radiologists and radiology techniciansworldwide, creating a bottleneck in timely and accurate diagnosis. Artificial Intelligence (AI) has emerged as a revolutionarytool in the field of radiology, particularly as a decision support system for radiology technicians. While much of the AI researchin medical imaging focuses on automating radiologist tasks, the integration of AI tools into radiology technician workflowspresents a valuable, underexplored frontier. This paper investigates the role of AI in assisting radiology technicians by enhancingimage acquisition quality, automating repetitive tasks, supporting error detection, and optimizing workflow management. It alsodiscusses AI’s contribution to patient safety, data annotation, training, and real-time support during imaging procedures. As AItechnology evolves, radiology technicians are increasingly becoming empowered with tools that boost accuracy, improveefficiency, and reduce burnout. The paper also examines ethical, technical, and operational considerations in deploying AIsystems in radiological environments, concluding with insights into the future of collaborative human-AI integration in medicalimaging.