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

Douglas Hackworth; Prashanth Dumpuri; Michael I. Miga

doi:10.1117/12.811922

13 March 2009 A dual compute resource strategy for computational model-assisted therapeutic interventions

Douglas Hackworth, Prashanth Dumpuri, Michael I. Miga

Proceedings Volume 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling; 72612R (2009) https://doi.org/10.1117/12.811922
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

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.

Citation Download Citation

Douglas Hackworth, Prashanth Dumpuri, and Michael I. Miga "A dual compute resource strategy for computational model-assisted therapeutic interventions", Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 72612R (13 March 2009); https://doi.org/10.1117/12.811922

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