ROS-IGTL-Bridge: an open network interface for image-guided therapy using the ROS environment

Purpose With the growing interest in advanced image-guidance for surgical robot systems, rapid integration and testing of robotic devices and medical image computing software are becoming essential in the research and development. Maximizing the use of existing engineering resources built on widely...

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Bibliographic Details
Published in:International journal for computer assisted radiology and surgery 2017-08, Vol.12 (8), p.1451-1460
Main Authors: Frank, Tobias, Krieger, Axel, Leonard, Simon, Patel, Niravkumar A., Tokuda, Junichi
Format: Article
Language:English
Subjects:
Computation
Computer Imaging
Computer Science
Construction standards
Data retrieval
Data transfer (computers)
Health Informatics
Imaging
Information sharing
IP (Internet Protocol)
Medical electronics
Medical research
Medicine
Medicine & Public Health
Messages
Original Article
Pattern Recognition and Graphics
Performance tests
Platforms
Pricing policies
Product development
Prototyping
R&D
Radiology
Research & development
Robots
Software
Strings
Surgery
TCP (protocol)
TCP/IP (protocol)
Vision
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Summary:Purpose With the growing interest in advanced image-guidance for surgical robot systems, rapid integration and testing of robotic devices and medical image computing software are becoming essential in the research and development. Maximizing the use of existing engineering resources built on widely accepted platforms in different fields, such as robot operating system (ROS) in robotics and 3D Slicer in medical image computing could simplify these tasks. We propose a new open network bridge interface integrated in ROS to ensure seamless cross-platform data sharing. Methods A ROS node named ROS-IGTL-Bridge was implemented. It establishes a TCP/IP network connection between the ROS environment and external medical image computing software using the OpenIGTLink protocol. The node exports ROS messages to the external software over the network and vice versa simultaneously, allowing seamless and transparent data sharing between the ROS-based devices and the medical image computing platforms. Results Performance tests demonstrated that the bridge could stream transforms, strings, points, and images at 30 fps in both directions successfully. The data transfer latency was
ISSN:1861-6410
1861-6429
DOI:10.1007/s11548-017-1618-1