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Proceedings Paper

A system for visualization and automatic placement of the endoclamp balloon catheter
Author(s): Hugo Furtado; Thomas Stüdeli; Mauro Sette; Eigil Samset; Borut Gersak
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Paper 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.

Paper Details

Date Published: 23 February 2010
PDF: 8 pages
Proc. SPIE 7625, Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling, 76250C (23 February 2010); doi: 10.1117/12.844100
Show Author Affiliations
Hugo Furtado, Jožef Stefan Institute (Slovenia)
Medical Univ. Vienna (Austria)
Thomas Stüdeli, Delft Univ. of Technology (Netherlands)
Mauro Sette, Katholieke Univ. Leuven (Belgium)
Eigil Samset, Univ. of Oslo (Norway)
Borut Gersak, Univ. Medical Ctr. Ljubljana (Slovenia)

Published in SPIE Proceedings Vol. 7625:
Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling
Kenneth H. Wong; Michael I. Miga, Editor(s)

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