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Proceedings Paper

Intraoperative adaptation and visualization of preoperative risk analyses for oncologic liver surgery
Author(s): Christian Hansen; Stefan Schlichting; Stephan Zidowitz; Alexander Köhn; Milo Hindennach; Markus Kleemann; Heinz-Otto Peitgen
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Paper Abstract

Tumor resections from the liver are complex surgical interventions. With recent planning software, risk analyses based on individual liver anatomy can be carried out preoperatively. However, additional tumors within the liver are frequently detected during oncological interventions using intraoperative ultrasound. These tumors are not visible in preoperative data and their existence may require changes to the resection strategy. We propose a novel method that allows an intraoperative risk analysis adaptation by merging newly detected tumors with a preoperative risk analysis. To determine the exact positions and sizes of these tumors we make use of a navigated ultrasound-system. A fast communication protocol enables our application to exchange crucial data with this navigation system during an intervention. A further motivation for our work is to improve the visual presentation of a moving ultrasound plane within a complex 3D planning model including vascular systems, tumors, and organ surfaces. In case the ultrasound plane is located inside the liver, occlusion of the ultrasound plane by the planning model is an inevitable problem for the applied visualization technique. Our system allows the surgeon to focus on the ultrasound image while perceiving context-relevant planning information. To improve orientation ability and distance perception, we include additional depth cues by applying new illustrative visualization algorithms. Preliminary evaluations confirm that in case of intraoperatively detected tumors a risk analysis adaptation is beneficial for precise liver surgery. Our new GPU-based visualization approach provides the surgeon with a simultaneous visualization of planning models and navigated 2D ultrasound data while minimizing occlusion problems.

Paper Details

Date Published: 31 March 2008
PDF: 10 pages
Proc. SPIE 6918, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling, 691809 (31 March 2008); doi: 10.1117/12.770243
Show Author Affiliations
Christian Hansen, MeVis Research (Germany)
Stefan Schlichting, Univ. Hospital Schleswig-Holstein (Germany)
Stephan Zidowitz, MeVis Research (Germany)
Alexander Köhn, MeVis Research (Germany)
Milo Hindennach, MeVis Research (Germany)
Markus Kleemann, Univ. Hospital Schleswig-Holstein (Germany)
Heinz-Otto Peitgen, MeVis Research (Germany)


Published in SPIE Proceedings Vol. 6918:
Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling
Michael I. Miga; Kevin Robert Cleary, Editor(s)

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