AI-Powered 3D Reconstruction from 2D Scans

Abstract

Artificial intelligence (AI) is reshaping how medical images are interpreted and used in practice. Traditionally, clinicians rely on 2D radiological slices such as CT and MRI to infer 3D anatomical structures, a process that is mentally demanding and often variable between observers. With AI, these 2D slices can now be transformed into detailed, interactive 3D models in real time. Such models improve diagnostic accuracy, support surgical planning, and open new opportunities for precision medicine. This paper explores the principles, computational strategies, and future implications of AI-powered 3D reconstruction for clinical and research applications.