Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality


Rüdiger Göbl Rüdiger Göbl, M.Sc.

Technische Universität München
Fakultät für Informatik I16
Boltzmannstr. 3
85748 Garching b. München
Room: MI 03.13.044
Phone: +49 (89) 289-19412

Klinikum Rechts der Isar
Interdisziplinäres Forschungslabor
Ismaninger Str. 22
81675 München
Room: Building 501 - 01.3a-c
Phone: +49 89 4140 6457

Research Interests and Projects

  • Fields of Interest
    • Interventional Ultrasound
    • Ultrasound Reconstruction
    • Computer Vision
  • Research Project: Realtime Brain Shift Tracking and Tool Detection from Tri-Dimensional Ultrasound Data
  • Master's Thesis: Parametric and Statistical Models for Computational Sonography

Active Research Projects

SUPRA: Software Defined Ultrasound Processing for Real-Time Applications

SUPRA: Software Defined Ultrasound Processing for Real-Time Applications

SUPRA is an open-source pipeline for fully software defined ultrasound processing for real-time applications. Covering everything from beamforming to output of B-Mode images, SUPRA can help to improve the reproducibility of results and does allow for a full customization of the image acquisition workflow. Including all processing stages of a common ultrasound pipeline, it can be executed in 2D and 3D on consumer GPUs in real-time. Even on hardware as small as the CUDA enabled Jetson TX2, SUPRA allows for 2D imaging in real-time.

You can access the code on our github page:
Additional information can be found in our work on SUPRA
Göbl, R. and Navab, N. and Hennersperger, C., SUPRA: Open Source Software Defined Ultrasound Processing for Real-Time Applications, eprint arXiv:1711.06127, Nov 2017, under review for IPCAI2018
EDEN2020: Enhanced Delivery Ecosystem for Neurosurgery

EDEN2020: Enhanced Delivery Ecosystem for Neurosurgery

EDEN2020 (Enhanced Delivery Ecosystem for Neurosurgery) aims to develop the gold standard for one-stop diagnosis and treatment of brain disease by delivering an integrated technology platform for minimally invasive neurosurgery. A team of first-class industrial partners (Renishaw plc. and XoGraph ltd.), leading clinical oncological neurosurgery team (Università di Milano, San Raffaele and Politecnico di Milano) lead by Prof. Lorenzo Bello and the involvement of leading experts in shape sensing (Universitair Medisch Centrum Groningen) under supervision of Prof. Dr. Sarthak Misra The project is coordinated by Dr. Rodriguez y Baena, Imperial College London. His team provides the core technology for the envisioned system, the bendable robotic needle. During the course of EDEN2020 this interdisciplinary team will work on the integration of 5 key concepts, namely (1) pre-operative MRI and diffusion-MRI imaging, (2) intra-operative ultrasounds, (3) robotic assisted catheter steering, (4) brain diffusion modelling, and (5) a robotics assisted neurosurgical robotic product (the Neuromate), into a pre-commercial prototype which meets the pressing demand for better and less invasive neurosurgery. Our chair will be focusing on the imaging components (i.e. (1) and (2)), targeting the realtime compensation of tissue movement and accurate localization of the flexible catheters at hand. We will further extend the findings of FP7 ACTIVE, in which we successfully combined pre-operative MRI with intra-operative US through deformable 3D-2D registration, making us most qualified for this role.
Computational Sonography

Computational Sonography

3D ultrasound imaging has high potential for various clinical applications, but often suffers from high operator-dependency and the directionality of the acquired data. State-of-the-art systems mostly perform compounding of the image data prior to further processing and visualization, resulting in 3D volumes of scalar intensities. This work presents computational sonography as a novel concept to represent 3D ultrasound as tensor instead of scalar fields, mapping a full and arbitrary 3D acquisition to the reconstructed data. The proposed representation compactly preserves significantly more information about the anatomy-specific and direction-depend acquisition, facilitating both targeted data processing and improved visualization. We show the potential of this paradigm on ultrasound phantom data as well as on clinically acquired data for acquisitions of the femoral, brachial and antebrachial bone. Further investigation will consider additional compact directional-dependent representations on the one hand and on the other hand modify Computational Sonography from working on B-Mode images to RF-envelope statistics, motivated by the statistical process of image formation. We will show the advantages of the proposed improvements on simulated ultrasound data, phantom and clinically acquired ultrasound data.


R. Göbl, S. Virga, J. Rackerseder, B. Frisch, N. Navab, C. Hennersperger
Acoustic window planning for ultrasound acquisition
International Journal of Computer Assisted Radiology and Surgery / 8th International Conference on Information Processing in Computer-Assisted Interventions (IPCAI), Barcelona, Spain, June 2017.
The original publication is available online at


Finished Student Projects

Title: M.Sc.
Circumference of your head (in cm):  
Firstname: Rüdiger
Lastname: Göbl
Picture: Goebl_icon.jpg
Nationality: Blank
Groups: Registration/Visualization, Segmentation, Medical Imaging, IFL, Ultrasound
Position: Scientific Staff
Status: Active
Emailbefore: r.goebl
Room: MI 03.13.044
Telephone: +49 89 289 19412

Edit | Attach | Refresh | Diffs | More | Revision r1.16 - 02 Jan 2018 - 13:18 - RuedigerGoebl

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif