A systematic review of generative artificial intelligence techniques for synthetic medical image datasets: Quality, models, public availability and applications

Although the reviewed resources support diverse downstream applications, publicly available synthetic datasets and trained models remain scarce. Evaluation strategies vary widely, and the absence of standardized benchmarks limits cross-study comparisons and reliability assessment. To support reproducibility and responsible use of GAI in medical imaging, future work should prioritize the public release of curated synthetic resources, clearer guidance on model selection, and standardized, multi-dimensional evaluation frameworks.