In clinical MRI-guided interventions, the lack of high-quality peripheral equipment and specialized interventional MRI systems often necessitates delegating real-time control of MRI scanners to an assistant. We proposed a voice-based interaction system powered by large language models that enabled hands-free natural language control of MRI scanners. The system leveraged multi-agent collaboration driven by large language models to execute scanner functionalities, including sequence execution,…

