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HoloYolo: A proof‐of‐concept study for marker‐less surgical navigation of spinal rod implants with augmented reality and on‐device machine learning
Author(s) -
von Atzigen Marco,
Liebmann Florentin,
Hoch Armando,
Bauer David E.,
Snedeker Jess Gerrit,
Farshad Mazda,
Fürnstahl Philipp
Publication year - 2021
Publication title -
the international journal of medical robotics and computer assisted surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 53
eISSN - 1478-596X
pISSN - 1478-5951
DOI - 10.1002/rcs.2184
Subject(s) - computer science , augmented reality , artificial intelligence , computer vision , pointer (user interface) , virtual reality , ground truth , lumbosacral joint , proof of concept , benchmark (surveying) , surgery , medicine , operating system , geodesy , geography
Abstract 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.