29 citations · 115 across the 17 of their papers we have counts for
19 papers
Multi-task Localization and Segmentation for X-ray Guided Planning in Knee Surgery
Florian Kordon, Peter Fischer, Maxim Privalov +6
X-ray based measurement and guidance are commonly used tools in orthopaedic surgery to facilitate a minimally invasive workflow. Typically, a surgical planning is first performed u…
RinQ Fingerprinting: Recurrence-informed Quantile Networks for Magnetic Resonance Fingerprinting
Elisabeth Hoppe, Florian Thamm, Gregor Körzdörfer +6
Recently, Magnetic Resonance Fingerprinting (MRF) was proposed as a quantitative imaging technique for the simultaneous acquisition of tissue parameters such as relaxation times $T…
A Divide-and-Conquer Approach towards Understanding Deep Networks
Weilin Fu, Katharina Breininger, Roman Schaffert +2
Deep neural networks have achieved tremendous success in various fields including medical image segmentation. However, they have long been criticized for being a black-box, in that…
Analysis by Adversarial Synthesis -- A Novel Approach for Speech Vocoding
Ahmed Mustafa, Arijit Biswas, Christian Bergler +2
Classical parametric speech coding techniques provide a compact representation for speech signals. This affords a very low transmission rate but with a reduced perceptual quality o…
A 2D dilated residual U-Net for multi-organ segmentation in thoracic CT
Sulaiman Vesal, Nishant Ravikumar, Andreas Maier
Automatic segmentation of organs-at-risk (OAR) in computed tomography (CT) is an essential part of planning effective treatment strategies to combat lung and esophageal cancer. Acc…
Multi-task Learning for Chest X-ray Abnormality Classification on Noisy Labels
Sebastian Guendel, Florin C. Ghesu, Sasa Grbic +4
Chest X-ray (CXR) is the most common X-ray examination performed in daily clinical practice for the diagnosis of various heart and lung abnormalities. The large amount of data to b…