Sensorium: An Open-Source Multimodal Data Collection and Curation Library for Embodied Surgical AI· 手术AI的多模态数据开源库
Embodied surgical AI requires reliable multimodal data, yet surgical data collection remains costly, difficult to repeat, and strongly dependent on the hardware setup. We present Sensorium, an open-source Python library for recording, processing, annotating, and curating multimodal surgical data from configurable robot and sensor streams using the Robot Operating System (ROS) and ROS2 middleware. The library combines operator-facing data acquisition, configurable processing, semantic annotation, and episodic dataset generation. We evaluate Sensorium across 1516 recordings of phantom, ex vivo, and in vivo porcine experiments involving multiple surgical tasks and sensing configurations, and report preliminary usability feedback.
开源多模态数据库助力手术AI发展
- 核心方法
- 利用ROS及ROS2开发Sensorium库,实现多模态数据录制、处理、标注及生成
- 适合谁读
- 研究者、工程师
- 要解决的问题
- 解决手术AI多模态数据收集困难及成本高的问题
- 关键实验
- 评估了1516次涉及多种手术任务和传感配置的实验记录
- 主要贡献
- 提供了一个灵活配置、易于使用的多模态数据处理开源工具
- 意义与局限
- 对提高手术AI数据质量、促进研究有重要影响,但硬件依赖性依然存在