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将 3D Slicer 与 ROS2 桥接用于图像引导机器人手术干预。

Bridging 3D Slicer and ROS2 for Image-Guided Robotic Interventions.

机构信息

Whiting School of Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.

School of Computing, Queen's University, Kingston, ON K7L 3N6, Canada.

出版信息

Sensors (Basel). 2022 Jul 17;22(14):5336. doi: 10.3390/s22145336.

Abstract

Developing image-guided robotic systems requires access to flexible, open-source software. For image guidance, the open-source medical imaging platform 3D Slicer is one of the most adopted tools that can be used for research and prototyping. Similarly, for robotics, the open-source middleware suite robot operating system (ROS) is the standard development framework. In the past, there have been several "ad hoc" attempts made to bridge both tools; however, they are all reliant on middleware and custom interfaces. Additionally, none of these attempts have been successful in bridging access to the full suite of tools provided by ROS or 3D Slicer. Therefore, in this paper, we present the SlicerROS2 module, which was designed for the direct use of ROS2 packages and libraries within 3D Slicer. The module was developed to enable real-time visualization of robots, accommodate different robot configurations, and facilitate data transfer in both directions (between ROS and Slicer). We demonstrate the system on multiple robots with different configurations, evaluate the system performance and discuss an image-guided robotic intervention that can be prototyped with this module. This module can serve as a starting point for clinical system development that reduces the need for custom interfaces and time-intensive platform setup.

摘要

开发图像引导机器人系统需要使用灵活的开源软件。对于图像引导,开源医学成像平台 3D Slicer 是使用最多的工具之一,可用于研究和原型设计。同样,对于机器人技术,开源中间件套件机器人操作系统 (ROS) 是标准的开发框架。过去,已经有一些“特别”的尝试来连接这两种工具;然而,它们都依赖于中间件和自定义接口。此外,这些尝试都没有成功地连接到 ROS 或 3D Slicer 提供的全套工具。因此,在本文中,我们介绍了 SlicerROS2 模块,该模块旨在直接在 3D Slicer 中使用 ROS2 包和库。该模块的开发是为了实现机器人的实时可视化、适应不同的机器人配置,并促进双向的数据传输(在 ROS 和 Slicer 之间)。我们在具有不同配置的多个机器人上演示了该系统,评估了系统性能,并讨论了可以使用该模块进行原型设计的图像引导机器人干预。该模块可以作为临床系统开发的起点,减少对自定义接口和耗时的平台设置的需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ce6/9324680/bd2069e5f309/sensors-22-05336-g001.jpg

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