Equipped with state-of-the-art technology, we develop and optimize MRI pulse sequences to acquire quantitative MRI parameters at ultra-high resolutions. We work on reconstruction- and postprocessing algorithms to compensate for artifacts associated with high field strength MRI systems. These efforts include developing methods that handle physiological noise and head motion or designing schemes to reduce scan times. We also optimize the acquisition of data on highly specialized equipment, such as implementing spiral acquisition schemes for diffusion imaging on one of world-wide only three Connectom scanners, and of data for specific neuroscientific applications, such as functional imaging of the basal ganglia.

Teaser image for MRI biophysics

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. more

<span>Diffusion properties in cortical grey matter using inversion recovery diffusion weighted imaging</span>

Combined diffusion and T1 contrast can be used to explore the cortical grey matter structural complexity in the human brain in vivo. more

Quantification of transverse relaxation times of human cortical and subcortical structures in vivo at 7T

Transverse relaxation parameters are quantified in vivo for different cortical structures of the human brain at ultra-high field strength. more

Multi-Parameter Mapping for the NISCI Multi-Center Clinical Trial

Embedded in the clinical trial NISCI (Nogo inhibition in spinal cord injury:, we employ whole brain quantitative imaging at 3 Tesla as a new biomarker for de- and regeneration. more

fMRI of the Basal Ganglia at 7T using single- and multi-echo protocols

In order to study the Basal Ganglia in relation to cortical areas, the used fMRI protocol has to be carefully adjusted with respect to its region of interest and the necessary signal under-sampling. We performed a study at a field strength of 7 Tesla investigating the dependence of the detected signal on the MR parameters employed. more

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