Steffen Bollmann
Steffen Bollmann
Centre For Advanced Imaging, University of Queensland, Brisbane, Australia
Verified email at - Homepage
TitleCited byYear
Age dependent electroencephalographic changes in attention-deficit/hyperactivity disorder (ADHD)
SS Poil, S Bollmann, C Ghisleni, RL O’Gorman, P Klaver, J Ball, ...
Clinical Neurophysiology 125 (8), 1626-1638, 2014
The PhysIO toolbox for modeling physiological noise in fMRI data
L Kasper, S Bollmann, AO Diaconescu, C Hutton, J Heinzle, S Iglesias, ...
Journal of neuroscience methods 276, 56-72, 2017
Coupling between resting cerebral perfusion and EEG
RL O’Gorman, SS Poil, D Brandeis, P Klaver, S Bollmann, C Ghisleni, ...
Brain topography 26 (3), 442-457, 2013
Developmental changes in gamma-aminobutyric acid levels in attention-deficit/hyperactivity disorder
S Bollmann, C Ghisleni, SS Poil, E Martin, J Ball, D Eich-Höchli, ...
Translational psychiatry 5 (6), e589, 2015
Echo time‐dependent quantitative susceptibility mapping contains information on tissue properties
S Sood, J Urriola, D Reutens, K O’Brien, S Bollmann, M Barth, V Vegh
Magnetic resonance in medicine 77 (5), 1946-1958, 2017
Subcortical glutamate mediates the reduction of short-range functional connectivity with age in a developmental cohort
C Ghisleni, S Bollmann, SS Poil, D Brandeis, E Martin, L Michels, ...
Journal of Neuroscience 35 (22), 8433-8441, 2015
Effects of steroid hormones on sex differences in cerebral perfusion
C Ghisleni, S Bollmann, A Biason-Lauber, SS Poil, D Brandeis, E Martin, ...
PloS one 10 (9), e0135827, 2015
Age-dependent and-independent changes in attention-deficit/hyperactivity disorder (ADHD) during spatial working memory performance
S Bollmann, C Ghisleni, SS Poil, E Martin, J Ball, D Eich-Höchli, P Klaver, ...
The World Journal of Biological Psychiatry, 1-12, 2015
DeepQSM-using deep learning to solve the dipole inversion for MRI susceptibility mapping
KGB Rasmussen, MJ Kristensen, RG Blendal, LR Ostergaard, ...
Biorxiv, 278036, 2018
Assessment of microstructural signal compartments across the corpus callosum using multi-echo gradient recalled echo at 7 T
K Thapaliya, V Vegh, S Bollmann, M Barth
NeuroImage 182, 407-416, 2018
Pulsed arterial spin labelling at ultra-high field with a B1+-optimised adiabatic labelling pulse
F Zimmer, K O’Brien, S Bollmann, J Pfeuffer, K Heberlein, M Barth
Magnetic Resonance Materials in Physics, Biology and Medicine 29 (3), 463-473, 2016
Accelerated mapping of magnetic susceptibility using 3D planes‐on‐a‐paddlewheel (POP) EPI at ultra‐high field strength
D Stäb, S Bollmann, C Langkammer, K Bredies, M Barth
NMR in Biomedicine 30 (4), e3620, 2017
The challenge of bias‐free coil combination for quantitative susceptibility mapping at ultra‐high field
S Bollmann, SD Robinson, K O'brien, V Vegh, A Janke, L Marstaller, ...
Magnetic resonance in medicine 79 (1), 97-107, 2018
A 7T Human Brain Microstructure Atlas by Minimum Deformation Averaging at 300μm
AL Janke, K O'Brian, S Bollmann, T Kober, M Barth
ISMRM 2016, 2016
A GPU-accelerated performance optimized RAP-music algorithm for real-time source localization
C Dinh, J Rühle, S Bollmann, J Haueisen, D Güllmar
Biomedical Engineering/Biomedizinische Technik 57 (SI-1 Track-O), 808-808, 2012
DeepQSM-using deep learning to solve the dipole inversion for quantitative susceptibility mapping
S Bollmann, KGB Rasmussen, M Kristensen, RG Blendal, LR Østergaard, ...
NeuroImage 195, 373-383, 2019
Real-Time Clustered Multiple Signal Classification (RTC-MUSIC)
C Dinh, L Esch, J Rühle, S Bollmann, D Güllmar, D Baumgarten, ...
Brain topography 31 (1), 125-128, 2018
SHARQnet–Sophisticated harmonic artifact reduction in quantitative susceptibility mapping using a deep convolutional neural network
S Bollmann, MH Kristensen, MS Larsen, MV Olsen, MJ Pedersen, ...
Zeitschrift für Medizinische Physik 29 (2), 139-149, 2019
Non-linear Realignment Using Minimum Deformation Averaging for Single-subject fMRI at Ultra-high Field
S Bollmann, S Bollmann, A Puckett, A Janke, M Barth
Multimodal imaging in attention-deficit/hyperactivity disorder (ADHD)
S Bollmann
ETH Zurich, 2014
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