DeepcomplexMRI deep learnig reconstruction has been modified to process multi-echo MRI images. First results for different undersampling strategies suggest that performance is comparable to modern iterative algorithms like ENLIVE while taking only about 5 minutes to reconstruct a full 3D 1mm³/voxel resolved head image stack.
In this project, we studied cortical myelin in living humans at the spatial scale of cortical columns using high-resolution quantitative magnetic resonance imaging (MRI) methods at 7 T.
In this project, we study the resolution limits of different high-resolution functional magnetic resonance imaging (fMRI) methods to resolve differences within the cerebral cortex.
Understanding brain development and decline is of utmost importance in an aging society. MRI Biophysics Research Group aims to uncover crucial mechanisms of human brain aging, by identifying the contribution of iron accumulation, a major determinant of brain development and brain decline.
We linked the effective transverse relaxation rate R2* with dopaminergic cell densities and iron concentrations in nigrosome 1 by combining 3D quantitative iron histology, post mortem ultra-high resolution MRI, tissue deironing, and analytical modeling approaches.
We investigate the relationship between quantitative MRI (qMRI) at different cortical depths and cell counts, gene expression and white matter connections in the brain in order to provide novel biomarkers for tracking neurodegenerative diseases.
Robust U-fibre connectivity mapping can be achieved in vivo in the early visual processing stream using combined diffusion weighted imaging and functional retinotopy
We explore spatially resolved lipid imaging using matrix-assisted laser desorption/ionization (MALDI) as a method for validating MRI-based myelin biomarkers.