Clinical applications of generative artificial intelligence in radiology: image translation, synthesis, and text generation

Abstract

Abstract Generative artificial intelligence (AI) has enabled tasks in radiology, including tools for improving image quality. Recently, new hotspots have emerged, such as intra- or inter-modal image translation, task-specific image synthesis, and text generation. Advances in generative AI have facilitated the move towards low-dose, cost-effective, and high-quality radiological image acquisition. Large language models can aid radiologists by generating professional answers and facilitating patient-physician communications. However, radiologists must be aware of potential inaccuracies in the generated content and should only use such tools after rigorous validation of their performance.