Translational Surgical Oncology

Increasingly powerful technological developments in surgery like new devices and technologies provide a huge amount of valuable data which can be used to improve patient therapy. Although a lot of data is available, the numerous data sources are an overwhelming challenge for physicians, especially in the operating room.

We are an interdisciplinary research group including disciplines like computer science, engineering and medicine. Our research goal is to develop and evaluate computer- and robotic-assisted systems which optimize the surgical therapy of the individual patient by turning the available data into useful information.

Augmented Reality visualization by superimposing virtual images: Tumors (green), Vascular Tree (blue), Copyright: KIT.

Therefore, we are investigating the entire process chain along the surgical treatment path including pre-, intra- and postoperative patient information. Eligibility and success rates of surgeries can be improved using personalized digital representations of the patient and enable the deployment of this data in the operating room (OR), e.g. by visualization of planning data or the prediction of complications.

The research and methodological focuses are surgical workflow analysis, soft-tissue navigation and intraoperative visualization as well as surgical training and surgical data science. These methods allow for the first time a context-aware assistance in the OR of the future, which acts as an automatic information filter, avoids information overflow, adapts to the current needs of the surgeon and therefore provides the right information at the right time. In order to achieve this goal the close collaboration with interdisciplinary partners, in particular physicians, is necessary. Overall such systems have the potential to improve patient outcome and open up new possibilities to operate.

Contact

Prof. Dr. Stefanie Speidel
Translational Surgical Oncology
Phone: +49 (0)351 458 5413
E-Mail: Stefanie.speidel(at)nct-dresden.de

Prof. Dr. Stefanie Speidel (Copyright: André Wirsig)

Own recent publications

D. Katić, J. Schuck, A. Wekerle, H. Kenngott, B. Müller-Stich, R. Dillmann, S. Speidel: Bridging the gap between formal and experience-based knowledge for context-aware laparoscopy, International Journal of Computer Assisted Radiology and Surgery, 1-8, 2016

S. Bodenstedt, M. Wagner, B. Mayer, K. Stemmer, H. Kenngott, B Müller-Stich, R. Dillmann, S. Speidel: Image-based Laparoscopic Bowel Measurement. International Journal of Computer Assisted Radiology and Surgery, 11(3), 407-419, 2016

S. Suwelack, S. Röhl, S. Bodenstedt, D. Reichard, R. Dillmann, T. dos Santos, L. Maier-Hein, M. Wagner, J. Wünscher, H. Kenngott, B. Müller, S. Speidel: Physics-based shape matching for intraoperative image guidance, MedPhys, 41(11), 111901, 2014

H. Kenngott, M. Wagner, M. Gondan, F. Nickel, M. Nolden, A. Fetzer, J. Weitz, L. Fischer, S. Speidel, H. Meinzer, D. Böckler, M. Büchler, B. Müller-Stich. Real-time image guidance in laparoscopic liver surgery: first clinical experience with a guidance system based on intraoperative CT imaging. Surgical Endoscopy, 28(3), 933-940, 2014

D. Katic, A. Wekerle, J. Görtler, P. Spengler, S. Bodenstedt, S. Röhl, S. Suwelack, M. Wagner, H. Kenngott, B. Müller-Stich, R. Dillmann, S. Speidel: Context-Aware Augmented Reality in Laparoscopic Surgery. Computerized Medical Imaging and Graphics, 37(2):174-82, 2013

L. Maier-Hein, P. Mountney, A. Bartoli, H. Elhawary, D. Elson, A. Groch, A. Kolb, M. Rodrigues, J. Sorger, S. Speidel, D. Stoyanov: Optical Techniques for 3D Surface Reconstruction in Computer-assisted Laparoscopic Surgery. Medical Image Analysis, 17(8): 974–996, 2013