Intravascular modeling and navigation for stent graft installation based on data fusion between intravascular ultrasound and electromagnetic tracking sensor

This paper proposed a new vasculature modeling and navigation method based on the data fusion from intravascular ultrasound (IVUS) sensor and electromagnetic tracking sensor. Not only can we obtain the inner cross section images of blood vessels, but also capture the corresponding posture from the electromagnetic tracker. Then constructed the three dimensional models of blood vessels as part of the virtual reality navigation system for the deployment guidance of aortic stent graft. This guidance will facilitate the alignment of the holes on the stent graft with the renal and mesenteric arteries ramifications. First we integrated the hybrid probe consisting of those two sensors, and employed it to perform a scan inside a blood silicone model and captured data from both sensors. Then, proposed a new image processing method, which improves the gradient vector flow (GVF) method and combined it with multi-scale wavelet transformation, and performed kinematics with data filtering for reconstructing the virtual model, which was applied for navigation of stent graft installation after image registration. The development of such technology could reduce the time of installation and enable reduce contrast media needed for the surgery.