Lightweight distributed computing for intraoperative real-time image guidance

Stefan Suwelack; Darko Katic; Simon Wagner; Patrick Spengler; Sebastian Bodenstedt; Sebastian Röhl; Rüdiger Dillmann; Stefanie Speidel

doi:10.1117/12.911404

17 February 2012 Lightweight distributed computing for intraoperative real-time image guidance

Stefan Suwelack, Darko Katic, Simon Wagner, Patrick Spengler, Sebastian Bodenstedt, Sebastian Röhl, Rüdiger Dillmann, Stefanie Speidel

Author Affiliations +

Proceedings Volume 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling; 83162I (2012) https://doi.org/10.1117/12.911404
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

In order to provide real-time intraoperative guidance, computer assisted surgery (CAS) systems often rely on computationally expensive algorithms. The real-time constraint is especially challenging if several components such as intraoperative image processing, soft tissue registration or context aware visualization are combined in a single system. In this paper, we present a lightweight approach to distribute the workload over several workstations based on the OpenIGTLink protocol. We use XML-based message passing for remote procedure calls and native types for transferring data such as images, meshes or point coordinates. Two different, but typical scenarios are considered in order to evaluate the performance of the new system. First, we analyze a real-time soft tissue registration algorithm based on a finite element (FE) model. Here, we use the proposed approach to distribute the computational workload between a primary workstation that handles sensor data processing and visualization and a dedicated workstation that runs the real-time FE algorithm. We show that the additional overhead that is introduced by the technique is small compared to the total execution time. Furthermore, the approach is used to speed up a context aware augmented reality based navigation system for dental implant surgery. In this scenario, the additional delay for running the computationally expensive reasoning server on a separate workstation is less than a millisecond. The results show that the presented approach is a promising strategy to speed up real-time CAS systems.

Citation Download Citation

Stefan Suwelack, Darko Katic, Simon Wagner, Patrick Spengler, Sebastian Bodenstedt, Sebastian Röhl, Rüdiger Dillmann, and Stefanie Speidel "Lightweight distributed computing for intraoperative real-time image guidance", Proc. SPIE 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling, 83162I (17 February 2012); https://doi.org/10.1117/12.911404

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