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The correct placement of needles is decisive for the success of many minimally-invasive interventions and therapies. These needle insertions are usually only guided by radiological imaging and can benefit from additional navigation support. Augmented reality (AR) is a promising tool to conveniently provide needed information and may thus overcome the limitations of existing approaches. To this end, a prototypical AR application was developed to guide the insertion of needles to spinal targets using the mixed reality glasses Microsoft HoloLens. The system's registration accuracy was attempted to measure and three guidance visualisation concepts were evaluated concerning achievable in-plane and out-of-plane needle orientation errors in a comparison study. Results suggested high registration accuracy and showed that the AR prototype is suitable for reducing out-of-plane orientation errors. Limitations, like comparatively high in-plane orientation errors, effects of the viewing position and missing image slices indicate potential for improvement that needs to be addressed before transferring the application to clinical trials.

Based on coordinate measuring machine (CMM) the given part is measured in any orientation, and then the least square evaluation mathematical model of plane orientation tolerance is established. What’s more, the uncertainty evaluation method of orientation error is proposed according to the uncertainty theory of new geometrical product specification (GPS). The face-to-face angularity is taken as the example to present the effectiveness of the proposed uncertainty evaluation method. The result shows that the uncertainty evaluation method not only meets the requirements of new GPS standard, but also ensures the integrity of the flatness inspection results. As a result, the accuracy of the workpiece inspection can be improved.