PURPOSE: Optimal display of surgical planning data in the operating room is challenging. In liver surgery, an expressive and effective intraoperative visualization of 3D planning models is still a pressing need. The objective of this work is to visualize surgical planning information using a map display. METHODS: An approach for risk analysis and visualization of planning models is presented which provides relevant information at a glance without the need for user interaction. Therefore, we present methods for the identification and classification of critical anatomical structures in the proximity of a preoperatively planned resection surface. Shadow-like distance indicators are introduced to encode the distance from the resection surface to these critical structures on a risk map. The work is demonstrated with examples in liver resection surgery and evaluated within two user studies. RESULTS: The results of the performed user studies show that the proposed visualization techniques facilitate the process of risk assessment in liver resection surgery and might be a valuable extension to surgical navigations system. CONCLUSION: The approach provides a new and objective basis for the assessment of risks during liver surgery and has the potential to improve the outcome of surgical interventions.
PURPOSE: Optimal display of surgical planning data in the operating room is challenging. In liver surgery, an expressive and effective intraoperative visualization of 3D planning models is still a pressing need. The objective of this work is to visualize surgical planning information using a map display. METHODS: An approach for risk analysis and visualization of planning models is presented which provides relevant information at a glance without the need for user interaction. Therefore, we present methods for the identification and classification of critical anatomical structures in the proximity of a preoperatively planned resection surface. Shadow-like distance indicators are introduced to encode the distance from the resection surface to these critical structures on a risk map. The work is demonstrated with examples in liver resection surgery and evaluated within two user studies. RESULTS: The results of the performed user studies show that the proposed visualization techniques facilitate the process of risk assessment in liver resection surgery and might be a valuable extension to surgical navigations system. CONCLUSION: The approach provides a new and objective basis for the assessment of risks during liver surgery and has the potential to improve the outcome of surgical interventions.
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