259 citations · 307 across the 4 of their papers we have counts for
4 papers
'A net for everyone': fully personalized and unsupervised neural networks trained with longitudinal data from a single patient
Christian Strack, Kelsey L. Pomykala, Heinz-Peter Schlemmer +2
With the rise in importance of personalized medicine, we trained personalized neural networks to detect tumor progression in longitudinal datasets. The model was evaluated on two d…
FakeNews: GAN-based generation of realistic 3D volumetric data -- A systematic review and taxonomy
André Ferreira, Jianning Li, Kelsey L. Pomykala +3
With the massive proliferation of data-driven algorithms, such as deep learning-based approaches, the availability of high-quality data is of great interest. Volumetric data is ver…
k-strip: A novel segmentation algorithm in k-space for the application of skull stripping
Moritz Rempe, Florian Mentzel, Kelsey L. Pomykala +5
Objectives: Present a novel deep learning-based skull stripping algorithm for magnetic resonance imaging (MRI) that works directly in the information rich k-space. Materials and Me…
Medical Deep Learning -- A systematic Meta-Review
Jan Egger, Christina Gsaxner, Antonio Pepe +5
Deep learning (DL) has remarkably impacted several different scientific disciplines over the last few years. E.g., in image processing and analysis, DL algorithms were able to outp…