TY - GEN
T1 - A mixed-reality approach to radiation-free training of C-arm based surgery
AU - Stefan, Philipp
AU - Habert, Séverine
AU - Winkler, Alexander
AU - Lazarovici, Marc
AU - Fürmetz, Julian
AU - Eck, Ulrich
AU - Navab, Nassir
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85029520008&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-66185-8_61
DO - 10.1007/978-3-319-66185-8_61
M3 - Conference contribution
AN - SCOPUS:85029520008
SN - 9783319661841
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 540
EP - 547
BT - Medical Image Computing and Computer Assisted Intervention − MICCAI 2017 - 20th International Conference, Proceedings
A2 - Jannin, Pierre
A2 - Duchesne, Simon
A2 - Descoteaux, Maxime
A2 - Franz, Alfred
A2 - Collins, D. Louis
A2 - Maier-Hein, Lena
PB - Springer Verlag
T2 - 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017
Y2 - 11 September 2017 through 13 September 2017
ER -