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Proceedings Paper

A dual compute resource strategy for computational model-assisted therapeutic interventions
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Paper Abstract

Acquiring and incorporating intraoperative data into image-guided surgical systems has been shown to increase the accuracy of these systems and the accuracy of image-guided surgical procedures. Even with the advent of powerful computers and parallel clusters, the ability to integrate highly resolved computer model information in the planning and execution of image-guided surgery is challenging. More often than not, the computational times required to process preoperative models and incorporate intraoperative data for feedback are too cumbersome and do not meet the real time constraints of surgery, for both planning and intraoperative guidance. To decrease the computational time for the surgeon and minimize the resources in the operating room, we have developed a dual compute node framework for image-guided surgical procedures: (i) a high-capability compute resource which acts as a server to facilitate preoperative planning, and (ii) a low-capability compute resource which acts as a server node/compute node to process the intraoperative data and rapidly integrate the model-based analysis for therapeutic/surgical feedback. In this framework, the preoperative planning utilities and intraoperative guidance system act as client-nodes/graphics-nodes that are assisted by the model-assistant. Processed data is transferred back to the graphics node for planning display or intraoperative feedback depending on which resource is engaged. In order to efficiently manage the data and the computational resources we also developed a novel software manager. This dual-capability resource compute node concept and the software manager are reported in this work, and the low-capability resource compute node is investigated within the context of image-guided liver surgery using data acquired during hepatic tumor resection therapies. Preliminary results indicate that the dual node concept can significantly decrease the computational resources and time required for image-guided surgical procedures.

Paper Details

Date Published: 13 March 2009
PDF: 8 pages
Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 72612R (13 March 2009); doi: 10.1117/12.811922
Show Author Affiliations
Douglas Hackworth, Vanderbilt Univ. (United States)
Prashanth Dumpuri, Vanderbilt Univ. (United States)
Michael I. Miga, Vanderbilt Univ. (United States)

Published in SPIE Proceedings Vol. 7261:
Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling
Michael I. Miga; Kenneth H. Wong, Editor(s)

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