Example dataset for the hMRI toolbox MF Callaghan, A Lutti, J Ashburner, E Balteau, N Corbin, B Draganski, ... Data in brief 25, 104132, 2019 | 35 | 2019 |
hMRI–A toolbox for quantitative MRI in neuroscience and clinical research K Tabelow, E Balteau, J Ashburner, MF Callaghan, B Draganski, G Helms, ... Neuroimage 194, 191-210, 2019 | 245 | 2019 |
Model pathway diagrams for the representation of mathematical models T Koprucki, M Kohlhase, K Tabelow, D Müller, F Rabe Optical and Quantum Electronics 50, 1-9, 2018 | 10 | 2018 |
Magnetic resonance advection imaging of cerebrovascular pulse dynamics HU Voss, JP Dyke, K Tabelow, ND Schiff, DJ Ballon Journal of Cerebral Blood Flow & Metabolism 37 (4), 1223-1235, 2017 | 10 | 2017 |
Mathematical models as research data via flexiformal theory graphs M Kohlhase, T Koprucki, D Müller, K Tabelow Intelligent Computer Mathematics: 10th International Conference, CICM 2017 …, 2017 | 14 | 2017 |
Low SNR in diffusion MRI models J Polzehl, K Tabelow Journal of the American Statistical Association 111 (516), 1480-1490, 2016 | 28 | 2016 |
Mathematical research data T Koprucki, K Tabelow, I Kleinod PAMM 16 (1), 959-960, 2016 | 3 | 2016 |
Improving accuracy and temporal resolution of learning curve estimation for within-and across-session analysis M Deliano, K Tabelow, R König, J Polzehl PLoS One 11 (6), e0157355, 2016 | 9 | 2016 |
More specific signal detection in functional magnetic resonance imaging by false discovery rate control for hierarchically structured systems of hypotheses K Schildknecht, K Tabelow, T Dickhaus PloS one 11 (2), e0149016, 2016 | 12 | 2016 |
Mathematical models: A research data category? T Koprucki, K Tabelow Mathematical Software–ICMS 2016: 5th International Conference, Berlin …, 2016 | 8 | 2016 |
Evidence for early, non-lesional cerebellar damage in patients with multiple sclerosis: DTI measures correlate with disability, atrophy, and disease duration M Deppe, K Tabelow, J Krämer, JG Tenberge, P Schiffler, S Bittner, ... Multiple Sclerosis Journal 22 (1), 73-84, 2016 | 59 | 2016 |
Recovery of thalamic microstructural damage after Shiga toxin 2-associated hemolytic–uremic syndrome J Krämer, M Deppe, K Göbel, K Tabelow, H Wiendl, SG Meuth Journal of the neurological sciences 356 (1-2), 175-183, 2015 | 9 | 2015 |
Local estimation of the noise level in MRI using structural adaptation K Tabelow, HU Voss, J Polzehl Medical image analysis 20 (1), 76-86, 2015 | 35 | 2015 |
High-resolution diffusion kurtosis imaging at 3T enabled by advanced post-processing S Mohammadi, K Tabelow, L Ruthotto, T Feiweier, J Polzehl, N Weiskopf Frontiers in Neuroscience 8, 427, 2015 | 33 | 2015 |
POAS4SPM: a toolbox for SPM to denoise diffusion MRI data K Tabelow, S Mohammadi, N Weiskopf, J Polzehl Neuroinformatics 13, 19-29, 2015 | 21 | 2015 |
Adaptive smoothing of multi-shell diffusion weighted magnetic resonance data by msPOAS SMA Becker, K Tabelow, S Mohammadi, N Weiskopf, J Polzehl Neuroimage 95, 90-105, 2014 | 54 | 2014 |
Adaptive smoothing as inference strategy: more specificity for unequally sized or neighbouring regions M Welvaert, K Tabelow, R Seurinck, Y Rosseel Neuroinformatics 11, 435-445, 2013 | 7 | 2013 |
Position-orientation adaptive smoothing of diffusion weighted magnetic resonance data (POAS) SMA Becker, K Tabelow, HU Voss, A Anwander, RM Heidemann, ... Medical image analysis 16 (6), 1142-1155, 2012 | 71 | 2012 |
Modeling the orientation distribution function by mixtures of angular central Gaussian distributions K Tabelow, HU Voss, J Polzehl Journal of neuroscience methods 203 (1), 200-211, 2012 | 33 | 2012 |
Mathematical Methods for Signal and Image Analysis and Representation L Florack, R Duits, G Jongbloed, MC van Lieshout, L Davies Springer Science & Business Media, 2012 | 10 | 2012 |