7 citations · 15 across the 8 of their papers we have counts for
9 papers
Beyond Benchmarks: Using VLMs to Reveal Systematic Classification Failures Under Real World Conditions
Dieuwertje Alblas, Alma M. Liezenga, Jan Erik van Woerden +3
Verification and validation (V&V) of classification models is crucial to enable a wide range of sensor processing applications. Currently, the V&V process relies on time-consuming…
Geometric deep learning for local growth prediction on abdominal aortic aneurysm surfaces
Dieuwertje Alblas, Patryk Rygiel, Julian Suk +5
Abdominal aortic aneurysms (AAAs) are progressive focal dilatations of the abdominal aorta. AAAs may rupture, with a survival rate of only 20\%. Current clinical guidelines recomme…
Physics-informed graph neural networks for flow field estimation in carotid arteries
Julian Suk, Dieuwertje Alblas, Barbara A. Hutten +4
Hemodynamic quantities are valuable biomedical risk factors for cardiovascular pathology such as atherosclerosis. Non-invasive, in-vivo measurement of these quantities can only be…
Global Control for Local SO(3)-Equivariant Scale-Invariant Vessel Segmentation
Patryk Rygiel, Dieuwertje Alblas, Christoph Brune +2
Personalized 3D vascular models can aid in a range of diagnostic, prognostic, and treatment-planning tasks relevant to cardiovascular disease management. Deep learning provides a m…
SIRE: scale-invariant, rotation-equivariant estimation of artery orientations using graph neural networks
Dieuwertje Alblas, Julian Suk, Christoph Brune +2
Blood vessel orientation as visualized in 3D medical images is an important descriptor of its geometry that can be used for centerline extraction and subsequent segmentation and vi…
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…