MSc L.C. Liebrand
- PhD Candidate, Research Associate
- Main activities
- (Diffusion-weighted) Magnetic Resonance Imaging (MRI)
- Focus of research
Currently, I am working on neuroimaging for (ischemic) stroke at the Department of Biomedical Engineering and Physics. As a collaborator on the STAIRS (Stroke treatment decision support by Artificial Intelligence for analysis of MR images) project, my aim is to accelerate magnetic resonance imaging (MRI) and to simultaneously enable detection of stroke in the acute setting with aid of deep learning. In our group, we will develop an efficient way to combine different MRI modalities (e.g., diffusion-weighted MRI (dMRI), and fluid-attenuated inversion recovery (FLAIR)) into a useful tool for clinical decision making.
Previously, I investigated deep brain stimulation (DBS) for obsessive-compulsive disorder (OCD) and treatment-resistant depression (TRD) at the Department of Psychiatry. My focus was on finding the optimal target structures in white matter with dMRI (treatment optimization) and imaging-based prediction of individual treatment outcome (improved patient selection). In collaboration with the neurosurgeons, we updated the DBS targeting strategies for psychiatric DBS to include information on individual white matter structures.
My other interests include high-resolution and high-field (7T) dMRI and their application in research or in the clinic.