P. Stefan, S. Habert, A. Winkler, M. Lazarovici, J. Fuermetz, U. Eck, N. Navab A Mixed-Reality Approach to Radiation-free Training of C-arm based Surgery Proceedings of the 20th International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI), Quebec, Canada, September 2017. This work was nominated for the young scientist award at MICCAI 2017. The first two authors contribute equally to this paper. (bib)
	The discrepancy of continuously decreasing clinical training opportunities and increasing complexity of interventions in surgery has led to the development of different training options like anatomical models, computer-based simulators or cadaver trainings. However, trainees, following this training and ultimately performing patient treatment, still face a steep learning curve. To address this problem for C-arm based surgery, we introduce a realistic radiation-free simulation system that combines patient-based 3D printed anatomy and simulated X-ray imaging using a physical C-arm. This mixed reality simulation system facilitates a transition to C-arm based surgery and has the potential to complement or even replace large parts of cadaver training and to reduce the risk for errors when proceeding to patient treatment. In a technical evaluation, we show that our system simulates X-ray images accurately with an RMSE of 1.85 mm compared to real X-ray imaging. To explore the fidelity and usefulness of the proposed mixed reality system for training and assessment, we conducted a user study. Six surgical experts performed a facet joint injection on the simulator and rated aspects of the system on a 5-point Likert scale. They expressed agreement with the overall realism of the simulation and strong agreement with the usefulness of such a mixed reality system for training of novices and experts.
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