36 citations · 76 across the 10 of their papers we have counts for
10 papers
nnFoundation: 3D Foundation Models for Radiology
Constantin Ulrich Harsy, Tassilo Wald, Karol Gotkowski +80
Radiological artificial intelligence has advanced rapidly, yet most systems remain narrowly task-specific, data-intensive, and fragile under domain shift. Foundation models promise…
VINNA for Neonates -- Orientation Independence through Latent Augmentations
Leonie Henschel, David Kügler, Lilla Zöllei +1
Fast and accurate segmentation of neonatal brain images is highly desired to better understand and detect changes during development and disease. Yet, the limited availability of g…
FastSurfer-HypVINN: Automated sub-segmentation of the hypothalamus and adjacent structures on high-resolutional brain MRI
Santiago Estrada, David Kügler, Emad Bahrami +5
The hypothalamus plays a crucial role in the regulation of a broad range of physiological, behavioural, and cognitive functions. However, despite its importance, only a few small-s…
Estimating Head Motion from MR-Images
Clemens Pollak, David Kügler, Martin Reuter
Head motion is an omnipresent confounder of magnetic resonance image (MRI) analyses as it systematically affects morphometric measurements, even when visual quality control is perf…
Identifying and Combating Bias in Segmentation Networks by leveraging multiple resolutions
Leonie Henschel, David Kügler, Derek S Andrews +2
Exploration of bias has significant impact on the transparency and applicability of deep learning pipelines in medical settings, yet is so far woefully understudied. In this paper,…
Learning Anatomical Segmentations for Tractography from Diffusion MRI
Christian Ewert, David Kügler, Anastasia Yendiki +1
Deep learning approaches for diffusion MRI have so far focused primarily on voxel-based segmentation of lesions or white-matter fiber tracts. A drawback of representing tracts as v…