ArticleScientific reports2025
Proof of concept for voice based MRI scanner control using large language models in real time guided interventions.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Towards user-centered interactive medical image segmentation in VR with an assistive AI agent.Virtual reality · 2026Article
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Authors and funding
7 authors.
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Abstract
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, parameter adjustment, and scanner table positioning. In 90 hands-free tests for 18 predefined tasks performed within a real MRI scanning room, the system achieved an overall task completion rate of 93.3% (95% CI 86.2-96.9%). On a consumer laptop without GPU support, the response time for control commands was approximately 5-10.5 s. Our study demonstrates the feasibility of using large language models for voice-based interaction with MRI scanners during interventions, eliminating the need for additional assistants and allowing human-like communication.
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