59 citations · 224 across the 17 of their papers we have counts for
7 papers · 1 filter
What do neural networks learn in image classification? A frequency shortcut perspective
Shunxin Wang, Raymond Veldhuis, Christoph Brune +1
Frequency analysis is useful for understanding the mechanisms of representation learning in neural networks (NNs). Most research in this area focuses on the learning dynamics of NN…
Uncertainty-based quality assurance of carotid artery wall segmentation in black-blood MRI
Elina Thibeau-Sutre, Dieuwertje Alblas, Sophie Buurman +2
The application of deep learning models to large-scale data sets requires means for automatic quality assurance. We have previously developed a fully automatic algorithm for caroti…
Defocus Blur Synthesis and Deblurring via Interpolation and Extrapolation in Latent Space
Ioana Mazilu, Shunxin Wang, Sven Dummer +3
Though modern microscopes have an autofocusing system to ensure optimal focus, out-of-focus images can still occur when cells within the medium are not all in the same focal plane,…
RDA-INR: Riemannian Diffeomorphic Autoencoding via Implicit Neural Representations
Sven Dummer, Nicola Strisciuglio, Christoph Brune
Diffeomorphic registration frameworks such as Large Deformation Diffeomorphic Metric Mapping (LDDMM) are used in computer graphics and the medical domain for atlas building, statis…
A Survey on the Robustness of Computer Vision Models against Common Corruptions
Shunxin Wang, Raymond Veldhuis, Christoph Brune +1
The performance of computer vision models are susceptible to unexpected changes in input images caused by sensor errors or extreme imaging environments, known as common corruptions…
Implicit Neural Representations for Modeling of Abdominal Aortic Aneurysm Progression
Dieuwertje Alblas, Marieke Hofman, Christoph Brune +2
Abdominal aortic aneurysms (AAAs) are progressive dilatations of the abdominal aorta that, if left untreated, can rupture with lethal consequences. Imaging-based patient monitoring…
SE(3) symmetry lets graph neural networks learn arterial velocity estimation from small datasets
Julian Suk, Christoph Brune, Jelmer M. Wolterink
Hemodynamic velocity fields in coronary arteries could be the basis of valuable biomarkers for diagnosis, prognosis and treatment planning in cardiovascular disease. Velocity field…