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• W4206935169 abstract "The instrumentation of spinal fusion surgeries includes pedicle screw placement and rod implantation. While several surgical navigation approaches have been proposed for pedicle screw placement, less attention has been devoted towards the guidance of patient-specific adaptation of the rod implant. We propose a marker-free and intuitive Augmented Reality (AR) approach to navigate the bending process required for rod implantation. A stereo neural network is trained from the stereo video streams of the Microsoft HoloLens in an end-to-end fashion to determine the location of corresponding pedicle screw heads. From the digitized screw head positions, the optimal rod shape is calculated, translated into a set of bending parameters, and used for guiding the surgeon with a novel navigation approach. In the AR-based navigation, the surgeon is guided step-by-step in the use of the surgical tools to achieve an optimal result. We have evaluated the performance of our method on human cadavers against two benchmark methods, namely conventional freehand bending and marker-based bending navigation in terms of bending time and rebending maneuvers. We achieved an average bending time of 231s with 0.6 rebending maneuvers per rod compared to 476s (3.5 rebendings) and 348s (1.1 rebendings) obtained by our freehand and marker-based benchmarks, respectively." @default.
• W4206935169 created "2022-01-26" @default.
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• W4206935169 date "2022-04-01" @default.
• W4206935169 modified "2023-10-06" @default.
• W4206935169 title "Marker-free surgical navigation of rod bending using a stereo neural network and augmented reality in spinal fusion" @default.
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• W4206935169 doi "https://doi.org/10.1016/j.media.2022.102365" @default.
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