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

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autoren

  • Tobias Frank
  • Axel Krieger
  • Simon Leonard
  • Niravkumar A. Patel
  • Junichi Tokuda

Organisationseinheiten

Externe Organisationen

  • Children's National Medical Center
  • Johns Hopkins University
  • Worcester Polytechnic Institute
  • Harvard University
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Details

OriginalspracheEnglisch
Seiten (von - bis)1451-1460
Seitenumfang10
FachzeitschriftInternational journal of computer assisted radiology and surgery
Jahrgang12
Ausgabenummer8
PublikationsstatusVeröffentlicht - 1 Aug. 2017

Abstract

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 <1.2 ms for transforms, strings and points, and 25.2 ms for color VGA images. A separate test also demonstrated that the bridge could achieve 900 fps for transforms. Additionally, the bridge was demonstrated in two representative systems: a mock image-guided surgical robot setup consisting of 3D slicer, and Lego Mindstorms with ROS as a prototyping and educational platform for IGT research; and the smart tissue autonomous robot surgical setup with 3D Slicer. Conclusion: The study demonstrated that the bridge enabled cross-platform data sharing between ROS and medical image computing software. This will allow rapid and seamless integration of advanced image-based planning/navigation offered by the medical image computing software such as 3D Slicer into ROS-based surgical robot systems.

ASJC Scopus Sachgebiete

Zitieren

ROS-IGTL-Bridge: an open network interface for image-guided therapy using the ROS environment. / Frank, Tobias; Krieger, Axel; Leonard, Simon et al.
in: International journal of computer assisted radiology and surgery, Jahrgang 12, Nr. 8, 01.08.2017, S. 1451-1460.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Frank T, Krieger A, Leonard S, Patel NA, Tokuda J. ROS-IGTL-Bridge: an open network interface for image-guided therapy using the ROS environment. International journal of computer assisted radiology and surgery. 2017 Aug 1;12(8):1451-1460. doi: 10.1007/s11548-017-1618-1
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title = "ROS-IGTL-Bridge: an open network interface for image-guided therapy using the ROS environment",
abstract = "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 <1.2 ms for transforms, strings and points, and 25.2 ms for color VGA images. A separate test also demonstrated that the bridge could achieve 900 fps for transforms. Additionally, the bridge was demonstrated in two representative systems: a mock image-guided surgical robot setup consisting of 3D slicer, and Lego Mindstorms with ROS as a prototyping and educational platform for IGT research; and the smart tissue autonomous robot surgical setup with 3D Slicer. Conclusion: The study demonstrated that the bridge enabled cross-platform data sharing between ROS and medical image computing software. This will allow rapid and seamless integration of advanced image-based planning/navigation offered by the medical image computing software such as 3D Slicer into ROS-based surgical robot systems.",
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note = "Funding information: This study was supported in part by the National Institutes of Health (R01EB020667, R01CA111288, R01EB020610, P41EB015898). The authors thank Mr. Longquan Chen of Brigham and Women{\textquoteright}s Hospital for his technical support. The authors also thank Ms. Christina Choi for evaluating the rapid prototyping platform with Lego Mindstorms.",
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Download

TY - JOUR

T1 - ROS-IGTL-Bridge

T2 - an open network interface for image-guided therapy using the ROS environment

AU - Frank, Tobias

AU - Krieger, Axel

AU - Leonard, Simon

AU - Patel, Niravkumar A.

AU - Tokuda, Junichi

N1 - Funding information: This study was supported in part by the National Institutes of Health (R01EB020667, R01CA111288, R01EB020610, P41EB015898). The authors thank Mr. Longquan Chen of Brigham and Women’s Hospital for his technical support. The authors also thank Ms. Christina Choi for evaluating the rapid prototyping platform with Lego Mindstorms.

PY - 2017/8/1

Y1 - 2017/8/1

N2 - 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 <1.2 ms for transforms, strings and points, and 25.2 ms for color VGA images. A separate test also demonstrated that the bridge could achieve 900 fps for transforms. Additionally, the bridge was demonstrated in two representative systems: a mock image-guided surgical robot setup consisting of 3D slicer, and Lego Mindstorms with ROS as a prototyping and educational platform for IGT research; and the smart tissue autonomous robot surgical setup with 3D Slicer. Conclusion: The study demonstrated that the bridge enabled cross-platform data sharing between ROS and medical image computing software. This will allow rapid and seamless integration of advanced image-based planning/navigation offered by the medical image computing software such as 3D Slicer into ROS-based surgical robot systems.

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