713 citations · 1.4k across the 13 of their papers we have counts for
13 papers
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…
An automated, geometry-based method for hippocampal shape and thickness analysis
Kersten Diers, Hannah Baumeister, Frank Jessen +3
The hippocampus is one of the most studied neuroanatomical structures due to its involvement in attention, learning, and memory as well as its atrophy in ageing, neurological, and…
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…
Rapid head-pose detection for automated slice prescription of fetal-brain MRI
Malte Hoffmann, Esra Abaci Turk, Borjan Gagoski +8
In fetal-brain MRI, head-pose changes between prescription and acquisition present a challenge to obtaining the standard sagittal, coronal and axial views essential to clinical ass…
Automated Olfactory Bulb Segmentation on High Resolutional T2-Weighted MRI
Santiago Estrada, Ran Lu, Kersten Diers +5
The neuroimage analysis community has neglected the automated segmentation of the olfactory bulb (OB) despite its crucial role in olfactory function. The lack of an automatic proce…
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…
FatSegNet : A Fully Automated Deep Learning Pipeline for Adipose Tissue Segmentation on Abdominal Dixon MRI
Santiago Estrada, Ran Lu, Sailesh Conjeti +4
Purpose: Development of a fast and fully automated deep learning pipeline (FatSegNet) to accurately identify, segment, and quantify abdominal adipose tissue on Dixon MRI from the R…
Competition vs. Concatenation in Skip Connections of Fully Convolutional Networks
Santiago Estrada, Sailesh Conjeti, Muneer Ahmad +2
Increased information sharing through short and long-range skip connections between layers in fully convolutional networks have demonstrated significant improvement in performance…
Complex Fully Convolutional Neural Networks for MR Image Reconstruction
Muneer Ahmad Dedmari, Sailesh Conjeti, Santiago Estrada +3
Undersampling the k-space data is widely adopted for acceleration of Magnetic Resonance Imaging (MRI). Current deep learning based approaches for supervised learning of MRI image r…
DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy
Christian Wachinger, Martin Reuter, Tassilo Klein
We introduce DeepNAT, a 3D Deep convolutional neural network for the automatic segmentation of NeuroAnaTomy in T1-weighted magnetic resonance images. DeepNAT is an end-to-end learn…