activity
20172023
most citedMore Alike than Different: Quantifying Deviations of Brain Structure and Function in Major Depressive Disorder across Neuroimaging Modalities

7 citations · 16 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2023

Deepbet: Fast brain extraction of T1-weighted MRI using Convolutional Neural Networks

Lukas Fisch, Stefan Zumdick, Carlotta Barkhau +8

Brain extraction in magnetic resonance imaging (MRI) data is an important segmentation step in many neuroimaging preprocessing pipelines. Image segmentation is one of the research…

cs.LG20233 cited

From Group-Differences to Single-Subject Probability: Conformal Prediction-based Uncertainty Estimation for Brain-Age Modeling

Jan Ernsting, Nils R. Winter, Ramona Leenings +13

The brain-age gap is one of the most investigated risk markers for brain changes across disorders. While the field is progressing towards large-scale models, recently incorporating…

q-bio.NC20217 cited

More Alike than Different: Quantifying Deviations of Brain Structure and Function in Major Depressive Disorder across Neuroimaging Modalities

Nils R. Winter, Ramona Leenings, Jan Ernsting +28

Introduction: Identifying neurobiological differences between patients suffering from Major Depressive Disorder (MDD) and healthy individuals has been a mainstay of clinical neuros…

eess.SY20216 cited

Towards a Network Control Theory of Electroconvulsive Therapy Response

Tim Hahn, Hamidreza Jamalabadi, Erfan Nozari +24

Electroconvulsive Therapy (ECT) is arguably the most effective intervention for treatment-resistant depression. While large interindividual variability exists, a theory capable of…

q-bio.QM2017

Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging

Dmitry Petrov, Boris A. Gutman, Shih-Hua +72

As very large studies of complex neuroimaging phenotypes become more common, human quality assessment of MRI-derived data remains one of the last major bottlenecks. Few attempts ha…