使用实时指导干预的大型语言模型进行基于语音的MRI扫描仪控制的概念验证
Hui Chen1,2, Moritz Gutt3,4, Othmar Alexander Belker3,4
1Department of Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany. chen.hui@mh-hannover.de.
Scientific reports
|August 25, 2025
概括
使用大型语言模型的新语音控制系统可以在干预期间自由操作MRI扫描仪. 这项技术通过实现自然语言命令来提高效率,减少了对额外人员的需求.
科学领域:
- 医学成像
- 人工智能
背景情况:
- 由于设备的局限性,临床MRI指导干预通常需要专门的助手来控制扫描仪.
- 实时控制MRI扫描仪在干预环境中至关重要但具有挑战性.
研究的目的:
- 开发和评估基于语音的MRI扫描仪控制系统.
- 在干预性MRI中利用大语言模型 (LLM) 来执行自然语言命令.
主要方法:
- 为控制MRI扫描仪的功能而开发了一种多代理的LLM系统.
- 该系统在一个真正的MRI扫描室中进行了18项预定义任务的测试,共计90次无手试验.
主要成果:
- 在无手试验中,语音系统实现了93.3%的任务完成率.
- 在没有GPU支持的消费者笔记本电脑上,命令响应时间从5到10.5秒不等.
结论:
- 在干预期间,LLM可以实现基于语音的MRI扫描仪交互.
- 这种系统为减少对人类助理的依赖和改善程序中的沟通提供了潜在的解决方案.
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