A universal calibration framework for mixed-reality assisted surgery

Area of Science:

• Medical Technology
• Surgical Navigation
• Mixed Reality

Background:

• Mixed-reality (MR) surgery offers real-time 3D visualization for improved surgical planning and intraoperative adjustments.
• Sub-millimetre accuracy in MR visualization is critical for mitigating risks and enhancing precision in surgical procedures.

Purpose of the Study:

• To develop a device-agnostic, robust calibration method for sub-millimetre accuracy in MR camera-to-world registration.
• To address uncertainties in mixed-reality camera calibration for hologram-to-patient anatomy registration.

Main Methods:

• Utilized surgical navigation systems (NAV) for hand-eye calibration to localize the MR camera.
• Integrated and tested the calibration method in a representative surgical system with varied 2D and 3D camera trajectories.

Main Results:

• Achieved positional errors as low as 0.2 mm with a standard error of 0.2 mm, demonstrating robustness against camera motion.
• The calibration method meets the stringent accuracy and stability requirements for surgical applications.

Conclusions:

• The fiducial-based hand-eye calibration method integrates surgical navigation system accuracy into MR camera systems for intraoperative use.
• This high-precision approach is critical for improving surgical navigation and patient outcomes in mixed-reality-assisted surgery.