Robotic Ultrasound

With surgical interventions becoming more and more complex, there is an increasing need for image guidance solutions in the OR. While X-ray systems expose the surgical staff to significant ionizing radiation, and the usage of bulky MRI scanners is regularly not feasible, ultrasound (US) systems could offer a practical and economic solution. However, ultrasound imaging is less straight-forward in terms of manual handling of the transducer and the achievable image quality, and therefore highly depends on the experience and the dexterity of the operating physician. We believe that automatic robotic support for image-guided navigation can overcome these challenges in the operating theater.

Robotic US for Needle Guidance

Interventional robotic 3D ultrasound acquisition of a spine phantom (red) registered with CT image for interventional guidance, e.g. facet joint needle insertion.

In this project, we are investigating ways to perform automatic robotic US acquisitions, including automatic trajectory planning for optimal organ coverage, trajectory execution with force control for sufficient acoustic coupling, 3D compounding, automatic needle guidance and inseration, as well as visual servoing-inspired control laws to track both moving anatomy and moving tools and to update the trajectory in real-time.

Abdominal Robotic US Acquisition

Internal torque sensors of the robot and force control schemes allow safe ultrasound acquisitions.

Update: First results of an ongoing clinical study (see publication below) demonstrate that robotic ultrasound-assisted facet joint insertions lead to success rates comparable to current clinical practice while lowering the X-ray dose and offering additional anatomical context for needle trajectory planning.

Have a look at our publications:

2018 [DOI] J. Esteban, W. Simson, S. Requena Witzig, A. Rienmüller, S. Virga, B. Frisch, O. Zettinig, D. Sakara, Y. Ryang, N. Navab, and C. Hennersperger, “Robotic ultrasound-guided facet joint insertion,” International Journal of Computer Assisted Radiology and Surgery, vol. 13, iss. 6, p. 895–904, 2018.
2017 [PDF] [DOI] C. Hennersperger, B. Fuerst, S. Virga, O. Zettinig, B. Frisch, T. Neff, and N. Navab, “Towards MRI-Based Autonomous Robotic US Acquisitions: A First Feasibility Study,” IEEE Transactions on Medical Imaging, vol. 36, iss. 2, p. 538–548, 2017.
2017 [DOI] O. Zettinig, B. Frisch, S. Virga, M. Esposito, A. Rienmüller, B. Meyer, C. Hennersperger, Y. Ryang, and N. Navab, “3D Ultrasound Registration-based Visual Servoing for Neurosurgical Navigation,” International Journal of Computer Assisted Radiology and Surgery, vol. 12, iss. 9, p. 1607–1619, 2017.
2016 [DOI] R. Kojcev, B. Fuerst, O. Zettinig, J. Fotouhi, S. C. Lee, B. Frisch, R. H. Taylor, E. Sinibaldi, and N. Navab, “Dual-robot ultrasound-guided needle placement: closing the planning-imaging-action loop,” International Journal of Computer Assisted Radiology and Surgery, vol. 11, iss. 6, p. 1173–1181, 2016.
2016 [PDF] [DOI] S. Virga, O. Zettinig, M. Esposito, K. Pfister, B. Frisch, T. Neff, N. Navab, and C. Hennersperger, “Automatic Force-Compliant Robotic Ultrasound Screening of Abdominal Aortic Aneurysms,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016, p. 508–513.
2016 [PDF] [DOI] O. Zettinig, B. Fuerst, R. Kojcev, M. Esposito, M. Salehi, W. Wein, J. Rackerseder, B. Frisch, and N. Navab, “Toward Real-time 3D Ultrasound Registration-based Visual Servoing for Interventional Navigation,” in IEEE International Conference on Robotics and Automation (ICRA), 2016, p. 945–950.