12 citations · 28 across the 3 of their papers we have counts for
5 papers
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…
End-to-End Learning-Based Ultrasound Reconstruction
Walter Simson, Rüdiger Göbl, Magdalini Paschali +4
Ultrasound imaging is caught between the quest for the highest image quality, and the necessity for clinical usability. Our contribution is two-fold: First, we propose a novel full…
Data Augmentation with Manifold Exploring Geometric Transformations for Increased Performance and Robustness
Magdalini Paschali, Walter Simson, Abhijit Guha Roy +4
In this paper we propose a novel augmentation technique that improves not only the performance of deep neural networks on clean test data, but also significantly increases their ro…
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…
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…