Kerstin Ritter geb. Hackmack
Kerstin Ritter geb. Hackmack
Bernstein Center for Computational Neuroscience, Charité-Universitätsmedizin Berlin
Verified email at bccn-berlin.de - Homepage
Title
Cited by
Cited by
Year
The role of neural impulse control mechanisms for dietary success in obesity
M Weygandt, K Mai, E Dommes, V Leupelt, K Hackmack, T Kahnt, ...
Neuroimage 83, 669-678, 2013
1032013
Impulse control in the dorsolateral prefrontal cortex counteracts post-diet weight regain in obesity
M Weygandt, K Mai, E Dommes, K Ritter, V Leupelt, J Spranger, ...
Neuroimage 109, 318-327, 2015
662015
Multi-scale classification of disease using structural MRI and wavelet transform
K Hackmack, F Paul, M Weygandt, C Allefeld, JD Haynes, ...
Neuroimage 62 (1), 48-58, 2012
632012
Can we overcome the ‘clinico-radiological paradox’in multiple sclerosis?
K Hackmack, M Weygandt, J Wuerfel, CF Pfueller, J Bellmann-Strobl, ...
Journal of neurology 259 (10), 2151-2160, 2012
522012
Multimodal prediction of conversion to Alzheimer's disease based on incomplete biomarkers
K Ritter, J Schumacher, M Weygandt, R Buchert, C Allefeld, JD Haynes, ...
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring 1 (2 …, 2015
462015
fMRI pattern recognition in obsessive–compulsive disorder
M Weygandt, CR Blecker, A Schäfer, K Hackmack, JD Haynes, D Vaitl, ...
Neuroimage 60 (2), 1186-1193, 2012
462012
MRI pattern recognition in multiple sclerosis normal-appearing brain areas
M Weygandt, K Hackmack, C Pfüller, J Bellmann–Strobl, F Paul, F Zipp, ...
PloS one 6 (6), e21138, 2011
432011
Visualizing convolutional networks for MRI-based diagnosis of Alzheimer’s disease
J Rieke, F Eitel, M Weygandt, JD Haynes, K Ritter
Understanding and Interpreting Machine Learning in Medical Image Computing …, 2018
242018
Layer-wise relevance propagation for explaining deep neural network decisions in MRI-based Alzheimer’s disease classification
M Böhle, F Eitel, M Weygandt, K Ritter
Frontiers in aging neuroscience 11, 194, 2019
212019
Stress-induced brain activity, brain atrophy, and clinical disability in multiple sclerosis
M Weygandt, L Meyer-Arndt, JR Behrens, K Wakonig, J Bellmann-Strobl, ...
Proceedings of the National Academy of Sciences 113 (47), 13444-13449, 2016
132016
Uncovering convolutional neural network decisions for diagnosing multiple sclerosis on conventional MRI using layer-wise relevance propagation
F Eitel, E Soehler, J Bellmann-Strobl, AU Brandt, K Ruprecht, RM Giess, ...
NeuroImage: Clinical 24, 102003, 2019
112019
Insulin action in the brain regulates mitochondrial stress responses and reduces diet-induced weight gain
K Wardelmann, S Blümel, M Rath, E Alfine, C Chudoba, M Schell, W Cai, ...
Molecular metabolism 21, 68-81, 2019
102019
Multivariate decoding of fMRI data: Towards a content-based cognitive neuroscience
J Heinzle, S Anders, S Bode, C Bogler, Y Chen, RM Cichy, K Hackmack, ...
Neuroforum 18 (1), 1-16, 2012
72012
Mental speed is associated with the shape irregularity of white matter MRI hyperintensity load
C Lange, P Suppa, A Mäurer, K Ritter, U Pietrzyk, E Steinhagen-Thiessen, ...
Brain imaging and behavior 11 (6), 1720-1730, 2017
52017
Combination of structural MRI and FDG-PET of the brain improves diagnostic accuracy in newly manifested cognitive impairment in geriatric inpatients
K Ritter, C Lange, M Weygandt, A Mäurer, A Roberts, M Estrella, P Suppa, ...
Journal of Alzheimer's Disease 54 (4), 1319-1331, 2016
52016
Testing the Robustness of Attribution Methods for Convolutional Neural Networks in MRI-Based Alzheimer’s Disease Classification
F Eitel, K Ritter, Alzheimer’s Disease Neuroimaging Initiative (ADNI
Interpretability of Machine Intelligence in Medical Image Computing and …, 2019
42019
MRI-based diagnostic biomarkers for early onset pediatric multiple sclerosis
M Weygandt, HM Hummel, K Schregel, K Ritter, C Allefeld, E Dommes, ...
NeuroImage: Clinical 7, 400-408, 2015
42015
GPx3 dysregulation impacts adipose tissue insulin receptor expression and sensitivity
R Hauffe, V Stein, C Chudoba, T Flore, M Rath, K Ritter, M Schell, ...
JCI insight 5 (11), 2020
32020
Predicting Fluid Intelligence in Adolescent Brain MRI Data: An Ensemble Approach
S Srivastava, F Eitel, K Ritter
Challenge in Adolescent Brain Cognitive Development Neurocognitive …, 2019
12019
Neural mechanisms of perceptual decision-making and their link to neuropsychiatric symptoms in multiple sclerosis
M Weygandt, J Behrens, J Brasanac, E Söder, L Meyer-Arndt, K Wakonig, ...
Multiple sclerosis and related disorders 33, 139-145, 2019
12019
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