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In the current clinical workflow of endovascular abdominal aortic repairs (EVAR) a stent graft is inserted into the aneurysmatic aorta under 2D angiographic imaging. Due to the missing depth information in the X-ray visualization, it is highly difficult in particular for junior physicians to place the stent graft in the preoperatively defined position within the aorta. Therefore, advanced 3D visualization of stent grafts is highly required. In this paper, we present a novel algorithm to automatically match a 3D model of the stent graft to an intraoperative 2D image showing the device. By automatic preprocessing and a globalto-local registration approach, we are able to abandon user interaction and still meet the desired robustness. The complexity of our registration scheme is reduced by a semi-simultaneous optimization strategy incorporating constraints that correspond to the geometric model of the stent graft. Via experiments on synthetic, phantom, and real interventional data, we are able to show that the presented method matches the stent graft model to the 2D image data with good accuracy.

The interlocking of intramedullary nails is a technically demanding procedure which involves a considerable amount of X-ray acquisitions; one study lists as many as 48 to successfully complete the procedure and fix screws into 4-6 mm distal holes of the nail. We propose to design an augmented radiolucent drill to assist surgeons in completing the distal locking procedure without any additional X-ray acquisitions. Using an augmented reality fluoroscope that coregisters optical and X-ray images, we exploit solely the optical images to detect the augmented radiolucent drill and estimate its tip position in real-time. Consequently, the surgeons will be able to maintain the down the beam positioning required to drill the screws into the nail holes successfully. To evaluate the accuracy of the proposed augmented drill, we perform a preclinical study involving six surgeons and ask them to perform distal locking on dry bone phantoms. Surgeons completed distal locking 98.3% of the time using only a single X-ray image with an average navigation time of 1.4 ± 0.9 min per hole.

All described measurements demonstrated valid measurement of lower limb alignment. With minimal effort, clinicians required only 3 X-ray image acquisitions using the augmented reality technology to achieve reliable mechanical axis deviation.