most citedFully Automatic Segmentation of 3D Brain Ultrasound: Learning from Coarse Annotations

4 citations · 4 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CV20194 cited

Fully Automatic Segmentation of 3D Brain Ultrasound: Learning from Coarse Annotations

Julia Rackerseder, Rüdiger Göbl, Nassir Navab +1

Intra-operative ultrasound is an increasingly important imaging modality in neurosurgery. However, manual interaction with imaging data during the procedures, for example to select…

cs.CV2018

Redefining Ultrasound Compounding: Computational Sonography

Rüdiger Göbl, Diana Mateus, Christoph Hennersperger +2

Freehand three-dimensional ultrasound (3D-US) has gained considerable interest in research, but even today suffers from its high inter-operator variability in clinical practice. Th…

cs.RO2018

Incremental Adversarial Learning for Optimal Path Planning

Salvatore Virga, Christian Rupprecht, Nassir Navab +1

Path planning plays an essential role in many areas of robotics. Various planning techniques have been presented, either focusing on learning a specific task from demonstrations or…

eess.IV2018

Initialize globally before acting locally: Enabling Landmark-free 3D US to MRI Registration

Julia Rackerseder, Maximilian Baust, Rüdiger Göbl +2

Registration of partial-view 3D US volumes with MRI data is influenced by initialization. The standard of practice is using extrinsic or intrinsic landmarks, which can be very tedi…

cs.CV2018

Markerless Inside-Out Tracking for Interventional Applications

Benjamin Busam, Patrick Ruhkamp, Salvatore Virga +4

Tracking of rotation and translation of medical instruments plays a substantial role in many modern interventions. Traditional external optical tracking systems are often subject t…