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Background Human-related factors affect the accuracy and safety of the oral and maxillofacial surgery (OMS). This study proposed an autonomous surgical system aiming to conduct the OMS under the assistance and surveillance of the surgeon. Methods A markerless navigation module and a compact OMS robot were seamlessly integrated into this system. The specifications of each module and the working concept of the system were elaborated in this paper. A drilling experiment was conducted on five 3D-printed mandible models to test the pose detecting capability and evaluate the operational performance. Results The experiment showed that this system could successfully guide the robot finishing the operation regardless of the mandible pose. The accuracy of software and hardware are acceptable and potential performance improvement can be achieved in positioning accuracy. Conclusion This system proposed a novel concept and a practical solution to decrease the human-related factors on the OMS, which may change the role of the surgeon in the future operating room and finally benefit the outcomes of OMS.

The patient was a 78-year-old man with a chief complaint of dysphagia. Extrinsic displacement of the posterior hypopharyngeal wall was observed on upper endoscopy. The patient was diagnosed with ossification of the anterior longitudinal ligament (OALL) of the cervical spine according to lateral cervical spine radiographic findings. The OALL caused dysphagia. In swallowing endoscopic assessments of patients with dysphagia, OALL of the cervical spine should be differentiated from other possible diagnoses by using radiography when extrinsic displacement of the posterior oropharyngeal or hypopharyngeal wall is observed.

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. Copyright © 2016 John Wiley & Sons, Ltd.