In robot-assisted endoscopic nasal surgery, due to the narrow and complex nasal cavity and sinus anatomical structure, the nasal endoscope of robot end-effector is prone to injure surrounding tissues during surgical approaches. In order to improve the safety of endoscope movement in robot-assisted endoscopic nasal surgery, this paper proposes a path planning method for endoscopic surgical approaches based on medical image pixel map searching, and safe surgical paths from the nasal entrance point to the operating areas are obtained. Firstly, through the trajectory analysis of nasal endoscope tip during surgery, the path planning requirements of endoscope tip are analyzed and obtained. Then, considering the narrow and complex anatomy of the nasal cavity, a binarized three-dimensional grid map containing the spatial anatomy of the nasal cavity is constructed based on the patient's CT medical image sequence. The endoscopic surgical approaches are searched and optimized by introducing the A-star algorithm, and safe surgical paths from the nasal entrance point to the operating areas are obtained. Finally, a virtual nasal endoscopy system is developed and tested on a head model containing nasal tissue, and the effectiveness of the planned surgical paths is verified by automatic virtual nasal endoscopy browsing experiment.

Percutaneous needle insertion is a widely used technique in needle-based intervention; however, it is difficult to achieve high targeting accuracy due to needle deflection and the boundary effect in multilayered tissues. This paper presents a preoperative needle insertion trajectory planning method that includes needle deflection modeling, insertion angle correction and needle trajectory optimization. The needle deflection model can predict the needle deflection with preoperatively obtained information, which includes tissue-specific parameters and the geometric/material properties of the needle. An insertion angle shift distribution model is obtained based on experimental data, and is used to correct insertion angles at tissue boundaries. The needle trajectory optimization is based on the weighted sum of cost function and balances the assessment criteria, which include the trajectory length, the insertion angle, and the distance to critical structures, and determines the needle trajectory with the best performance. Experiments are conducted to demonstrate that with the proposed preoperative needle insertion trajectory planning method, a needle insertion trajectory with increased accuracy, desired insertion length and safe distance to critical structures can be obtained.

In endoscopic nasal surgery, robots, rather than surgical assistants, can be introduced to hold endoscopes and act as the surgeon's third hand, which helps to reduce their operation burden. To address the problem of robot-assisted surgical field of view (FOV) acquisition in endoscopic nasal surgery, this paper proposes an automatic surgical FOV control method based on tracking motion for the entire surgical process to achieve efficient and safe surgical FOV acquisition. First, through the analysis of the spatial pose relationship between the nasal endoscope and the surgical instrument, the desired endoscope pose corresponding to the optimal surgical FOV during surgery is obtained. Then, an automatic surgical FOV control method based on tracking motion is proposed. For automatic FOV acquisition outside the nasal cavity, an unconstrained tracking motion control strategy is proposed. For automatic FOV acquisition inside the nasal cavity, a remote center of motion (RCM) constrained control strategy is proposed. Combined with the entire surgical process, the overall control framework of the surgical FOV during nasal surgery is established. After that, a virtual fixtures (VFs) model based on the CT data of the nasal cavity and a safety contact force threshold control method are proposed to improve the safety of robot motion. Finally, the robot-assisted maxillary sinus surgery experiment is carried out. The results show that the proposed automatic FOV control method can realize clear and safe automatic FOV acquisition during the entire surgical process so that the surgeon can realize the “one surgeon three hands” operation, which reduces the surgeon's operation burden.