AI in Radiology: Enhancing Diagnostic Accuracy and Workflow Efficiency

Abstract

AI is transforming radiology by improving diagnostic accuracy and streamlining workflows. This paper reviews the use of AI in analyzing medical imaging, including X-rays, MRIs, and CT scans, to detect conditions such as cancers, fractures, and neurological disorders. It highlights advancements in automated image segmentation, anomaly detection, and report generation. The discussion also addresses challenges, including the need for regulatory approval, integration into clinical workflows, and maintaining the role of radiologists in AI-assisted environments.