  Robot-assisted deployment of fenestrated stent grafts in Fenestrated
Endovascular Aortic Repair (FEVAR) requires accurate geometrical alignment.
Currently, this process is guided by 2D fluoroscopy, which is uninformative and
error prone. In this paper, a real-time framework is proposed to instantiate
the 3D shape of a fenestrated stent graft based on only a single low-dose 2D
fluoroscopic image. Firstly, the fenestrated stent graft was placed with
markers. Secondly, the 3D pose of each stent segment was instantiated by the
RPnP (Robust Perspective-n-Point) method. Thirdly, the 3D shape of the whole
stent graft was instantiated via graft gap interpolation. Focal-Unet was
proposed to segment the markers from 2D fluoroscopic images to achieve
semi-automatic marker detection. The proposed framework was validated on five
patient-specific 3D printed phantoms of aortic aneurysms and three stent grafts
with new marker placements, showing an average distance error of 1-3mm and an
average angle error of 4 degree.
