713 citations · 1.4k across the 13 of their papers we have counts for
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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,…
FastSurferVINN: Building Resolution-Independence into Deep Learning Segmentation Methods -- A Solution for HighRes Brain MRI
Leonie Henschel, David Kügler, Martin Reuter
Leading neuroimaging studies have pushed 3T MRI acquisition resolutions below 1.0 mm for improved structure definition and morphometry. Yet, only few, time-intensive automated imag…
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…
FastSurfer -- A fast and accurate deep learning based neuroimaging pipeline
Leonie Henschel, Sailesh Conjeti, Santiago Estrada +3
Traditional neuroimage analysis pipelines involve computationally intensive, time-consuming optimization steps, and thus, do not scale well to large cohort studies with thousands o…