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Pedicle Screw Placement Using an Augmented Reality Head-Mounted Display in a Porcine Model
Published on: May 24, 2024
Simulated augmented reality-based calibration of optical see-through head mound display for surgical navigation
Ho-Gun Ha1, Kyeongmo Gu1, Deokgi Jeung2
1Division of Intelligent Robot, Daegu Gyeongbuk Institute of Science and Technology (DGIST), 333 Techno Jungang-daero, Hyeonpung-myeon, Dalseong-gun, Daegu, 42988, Republic of Korea.
Purpose:
Calibration of an optical see-through head-mounted display is critical for augmented reality-based surgical navigation. While conventional methods have advanced, calibration errors remain significant. Moreover, prior research has focused primarily on calibration accuracy and procedure, neglecting the impact on the overall surgical navigation system. Consequently, these enhancements do not necessarily translate to accurate augmented reality in the optical see-through head mount due to systemic errors, including those in calibration.
Method:
This study introduces a simulated augmented reality-based calibration to address these issues. By replicating the augmented reality that appeared in the optical see-through head mount, the method achieves calibration that compensates for augmented reality errors, thereby reducing them. The process involves two distinct calibration approaches, followed by adjusting the transformation matrix to minimize displacement in the simulated augmented reality.
Results:
The efficacy of this method was assessed through two accuracy evaluations: registration accuracy and augmented reality accuracy. Experimental results showed an average translational error of 2.14 mm and rotational error of 1.06° across axes in both approaches. Additionally, augmented reality accuracy, measured by the overlay regions' ratio, increased to approximately 95%. These findings confirm the enhancement in both calibration and augmented reality accuracy with the proposed method.
Conclusion:
The study presents a calibration method using simulated augmented reality, which minimizes augmented reality errors. This approach, requiring minimal manual intervention, offers a more robust and precise calibration technique for augmented reality applications in surgical navigation.

