Image-guided cochlear implant surgery is expected to reduce volume of mastoidectomy, accelerate recovery, and improve safety. The purpose of this study was to investigate the safety and effectiveness of image-guided cochlear implant surgery by a non-invasive registration method, in a cadaveric study. We developed a visual positioning frame that can utilize the maxillary dentition as a registration tool and completed the tunnels experiment on 5 cadaver specimens (8 cases in total). The accuracy of the entry point and the target point were 0.471 ± 0.276 mm and 0.671 ± 0.268 mm, respectively. The shortest distance from the margin of the tunnel to the facial nerve and the ossicular chain were 0.790 ± 0.709 mm and 1.960 ± 0.630 mm, respectively. All facial nerves, tympanic membranes, and ossicular chains were completely preserved. Using this approach, high accuracy was achieved in this preliminary study, suggesting that the non-invasive registration method can meet the accuracy requirements for cochlear implant surgery. Based on the above accuracy, we speculate that our method can also be applied to neurosurgery, orbitofacial surgery, lateral skull base surgery, and anterior skull base surgery with satisfactory accuracy.
An optical see-through (OST) head-mounted display (HMD) is an appropriate option for an image-guided surgical navigation system (IGS) based on augmented reality (AR). However, the calibration of OST-HMDs has been challenging, since the augmented results can only be observed by the users wearing it. In this paper, we proposed an online calibration method based on the single-point active alignment method (SPAAM) for a HoloLens using a virtual tracking system. The transformation matrices between the world coordinates and the virtual holographic coordinates are calculated using a linear model and decomposed by the singular value decomposition (SVD) algorithm. The surgical workspace is analyzed, and there are nine sampling points for the offline calibration: eight at the vertices and one at the center of a cube of the workspace. 20 groups of data at each sampling point are collected. Five alignments should be implanted in the online calibration. The transformation matrices are compensated for the offset of every use of a HoloLens. To assess the accuracy of the calibration method, in accordance with the RANSAC algorithm, eight groups of additional data at random non-sampling locations are collected. Three different users that are familiar with the calibration procedures performed the calibration. The average distance error of our calibration was below 6 mm, and the rotation error was up to 5 •. It is a user-friendly, simple method for the online calibration of OST-HMDs. INDEX TERMS Optical see-through, augmented reality, HMD calibration.
Minimally invasive procedures are rapidly growing in popularity thanks to advancements in medical robots, visual navigation and space registration techniques. This paper presents a precise and efficient targeting method for robot-assisted percutaneous needle placement under Carm fluoroscopy. In this method, a special end-effector was constructed to perform fluoroscopy calibration and robot to image-space registration simultaneously. In addition, formulations were given to compute the movement of robot targeting and evaluate targeting accuracy using only one X-ray image. With these techniques, radiation exposure and operation time were reduced significantly compared to other commonly used methods. A pre-clinical experiment showed that the maximum angle error was 0.94 and the maximum position error of a target located 80mm below the end-effector was 1.31mm. And evaluation of the system in a robot-assisted pedicle screws placement surgery has justified the accuracy and reliability of proposed method in clinical applications.
Minimally invasive procedures are rapidly growing in popularity thanks to advancements in medical robots, visual navigation and space registration techniques. This paper presents a precise and efficient targeting method for robot-assisted percutaneous needle placement under Carm fluoroscopy. In this method, a special end-effector was constructed to perform fluoroscopy calibration and robot to image-space registration simultaneously. In addition, formulations were given to compute the movement of robot targeting and evaluate targeting accuracy using only one X-ray image. With these techniques, radiation exposure and operation time were reduced significantly compared to other commonly used methods. A pre-clinical experiment showed that the maximum angle error was 0.94 and the maximum position error of a target located 80mm below the end-effector was 1.31mm. And evaluation of the system in a robot-assisted pedicle screws placement surgery has justified the accuracy and reliability of proposed method in clinical applications.
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