Video see-through augmented reality for oral and maxillofacial surgery

Background: Oral and maxillofacial surgery has not been benefitting from image guidance techniques owing to the limitations in image registration. Methods: A real-time markerless image registration method is proposed by integrating a shape matching method into a 2D tracking framework. The image registration is performed by matching the patient's teeth model with intraoperative video to obtain its pose. The resulting pose is used to overlay relevant models from the same CT space on the camera video for augmented reality. Results: The proposed system was evaluated on mandible/maxilla phantoms, a volunteer and clinical data. Experimental results show that the target overlay error is about 1 mm, and the frame rate of registration update yields 3–5 frames per second with a 4 K camera. Conclusions: The significance of this work lies in its simplicity in clinical setting and the seamless integration into the current medical procedure with satisfactory response time and overlay accuracy.