About the course
- Neurosurgery: PD Dr. Jens Gempt and Dr. Kaywan Aftahy
- Urology: PD Dr. Matthias Heck and Dr. Kay Westenfelder
- Vascular Surgery: Dr. Reza Ghotbi
The course consists of three parts. In the first part, the participants will learn the basics of medical applications in image-guided surgery and interventions, in particular intraoperative imaging, medical augmented reality and surgical robotics. They gain the knowledge to understand the complex medical environment as well as its challenges in order to improve procedures with the focus on clinical workflow and imaging in the operating theatre of the future.
Then in the second part, the participants will be divided into groups of three. They will observe real image-guided surgeries at our clinical partner's sites. During this, they will analyze the procedures for potential improvements.
Finally, in the third part of the lecture, the groups will come up with a proposal on how to improve the current surgeries using Computer Vision, Augmented Reality or Robotics. They will present their findings in the lecture and use the feedback from discussions with the other participants and course organizers to come up with a sophisticated proposal.
Exposure to real-world problems, in particular observing an intervention at our clinical partner's sites makes this a unique setup for modeling and implementing creative solutions to improve patient care.
In this new type of real-world educational course participants will:
- learn the basics of some intraoperative imaging, medical augmented reality and surgical robotics explained in application examples
- learn how to move around in the operating theatre
- observe four real surgeries, document and analyze the procedure – from OR planning through patient anesthesia all the way to the suture
- directly communicate to the surgeons about the procedure
- develop a concept / solution to support procedures including interfaces, logistical approaches, use of technologies
- work in teams of 3 people analyzing these processes and come up with possible improvements (use of diagnostic imaging, logistical improvements, ...)
- try to translate that into an actual proposal for the surgical team
- final presentation including a proposal for a solution for the surgical teams
Fig.1. Pictures of IGS students from last semester (and Dr. Thomas Wendler) on the way to the surgery:
- As of today (25.04.2021), we are still planning to have mandatory visits to multiple surgeries at our clinical partners' sites. Due to the situation regarding the COVID-19 outbreak and the subsequent government measures, this might become impossible throughout the semester. In this case, the visits will be replaced by the study of recorded surgeries.
|28.04.2021||15:00 - 16:30||TUM Zoom||Introduction|
|03.05.2021||15:00 - 16:30||TUM Zoom||OR Training and Surgery Teasers||Dr. Thomas Wendler|
|05.05.2021||Group Assignment & start of OR scheduling||All students|
|05.05.2021||15:00 - 16:30||TUM Zoom||Intraoperative Imaging||Dr. Thomas Wendler|
|10.05.2021||15:00 - 16:30||TUM Zoom||Robotics||Prof. Mingchuan Zhou|
|12.05.2021||15:00 - 16:30||TUM Zoom||Augmented Reality||Matthias Grimm|
|17.05.2021||15:00 - 16:30||TUM Zoom||Tracking and Navigation||Ardit Ramadani|
|19.05.2021||15:00 - 16:30||TUM Zoom||Sonification||Sasan Matinfar|
|14.06.2021||15:00 - 16:30||TUM Zoom||Preliminary Presentation||All students|
|12.07.2021||15:00 - 16:30||TUM Zoom||Intermediate Presentation||All students|
|26.07.2021||15:00 - 16:30||TUM Zoom||Exam||Prof. Nassir Navab|
Some recommended readings
The following research papers show some examples of how modern computer vision, robotics, or augmented reality can be used to improve image guided surgeries. Off course this list is by no means exhaustive, but I think it can give you a lot of inspiration for your own ideas.
- Esteban, J., Simson, W., Witzig, S. R., Rienmüller, A., Virga, S., Frisch, B., ... & Hennersperger, C. (2018). Robotic ultrasound-guided facet joint insertion. International journal of computer assisted radiology and surgery, 13(6), 895-904.
- Roodaki, H., Filippatos, K., Eslami, A., & Navab, N. (2015, September). Introducing augmented reality to optical coherence tomography in ophthalmic microsurgery. In 2015 IEEE International Symposium on Mixed and Augmented Reality (pp. 1-6). IEEE.
- Matinfar, S., Nasseri, M. A., Eck, U., Kowalsky, M., Roodaki, H., Navab, N., ... & Navab, N. (2018). Surgical soundtracks: automatic acoustic augmentation of surgical procedures. International journal of computer assisted radiology and surgery, 13(9), 1345-1355.
- Esteban, J., Grimm, M., Unberath, M., Zahnd, G., & Navab, N. (2019, October). Towards fully automatic X-ray to CT registration. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 631-639). Springer, Cham.
- Nasseri, M. A., Eder, M., Nair, S., Dean, E. C., Maier, M., Zapp, D., ... & Knoll, A. (2013, July). The introduction of a new robot for assistance in ophthalmic surgery. In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 5682-5685). IEEE.
- Navab, N., Heining, S. M., & Traub, J. (2009). Camera augmented mobile C-arm (CAMC): calibration, accuracy study, and clinical applications. IEEE transactions on medical imaging, 29(7), 1412-1423.
- Padoy, N., Blum, T., Ahmadi, S. A., Feussner, H., Berger, M. O., & Navab, N. (2012). Statistical modeling and recognition of surgical workflow. Medical image analysis, 16(3), 632-641.
- Twinanda, A. P., Shehata, S., Mutter, D., Marescaux, J., De Mathelin, M., & Padoy, N. (2016). Endonet: A deep architecture for recognition tasks on laparoscopic videos. IEEE transactions on medical imaging, 36(1), 86-97.
- Matthies, P., Okur, A., Wendler, T., Navab, N., & Friebe, M. (2013, July). Combination of intra-operative freehand SPECT imaging with MR images for guidance and navigation. In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 3383-3386). IEEE.