HoloYolo: A proof‐of‐concept study for marker‐less surgical navigation of spinal rod implants with augmented reality and on‐device machine learning

Background Existing surgical navigation approaches of the rod bending procedure in spinal fusion rely on optical tracking systems that determine the location of placed pedicle screws using a hand‐held marker. Methods We propose a novel, marker‐less surgical navigation proof‐of‐concept to bending rod implants. Our method combines augmented reality with on‐device machine learning to generate and display a virtual template of the optimal rod shape without touching the instrumented anatomy. Performance was evaluated on lumbosacral spine phantoms against a pointer‐based navigation benchmark approach and ground truth data obtained from computed tomography. Results Our method achieved a mean error of 1.83 ± 1.10 mm compared to 1.87 ± 1.31 mm measured in the marker‐based approach, while only requiring 21.33 ± 8.80 s as opposed to 36.65 ± 7.49 s attained by the pointer‐based method. Conclusion Our results suggests that the combination of augmented reality and machine learning has the potential to replace conventional pointer‐based navigation in the future.