Title
A system for visualization and automatic placement of the endoclamp balloon catheter
Abstract
The European research network "Augmented Reality in Surgery" (ARIS*ER) developed a system that supports minimally invasive cardiac surgery based on augmented reality (AR) technology. The system supports the surgical team during aortic endoclamping where a balloon catheter has to be positioned and kept in place within the aorta. The presented system addresses the two biggest difficulties of the task: lack of visualization and difficulty in maneuvering the catheter. The system was developed using a user centered design methodology with medical doctors, engineers and human factor specialists equally involved in all the development steps. The system was implemented using the AR framework "Studierstube" developed at TU Graz and can be used to visualize in real-time the position of the balloon catheter inside the aorta. The spatial position of the catheter is measured by a magnetic tracking system and superimposed on a 3D model of the patient's thorax. The alignment is made with a rigid registration algorithm. Together with a user defined target, the spatial position data drives an actuator which adjusts the position of the catheter in the initial placement and corrects migrations during the surgery. Two user studies with a silicon phantom show promising results regarding usefulness of the system: the users perform the placement tasks faster and more accurately than with the current restricted visual support. Animal studies also provided a first indication that the system brings additional value in the real clinical setting. This work represents a major step towards safer and simpler minimally invasive cardiac surgery.
Year
DOI
Venue
2010
10.1117/12.844100
Proceedings of SPIE
Keywords
Field
DocType
Minimally Invasive Surgery,Cardiac Surgery,Augmented Reality,Robotics
Catheter,Minimally invasive cardiac surgery,Simulation,Visualization,Imaging phantom,Tracking system,Balloon,Augmented reality,Engineering,User-centered design
Conference
Volume
ISSN
Citations 
7625
0277-786X
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Hugo Furtado152.53
Thomas Stüdeli261.04
Mauro M. Sette391.91
Eigil Samset413316.57
Borut Gersak5114.36