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- DC 1: Intra-scan modulation with model-guided AI for accelerated diffusion MRI - University of Antwerp (Belgium) (pdf - 175 kB)
- DC 2: Deep learning-augmented super resolution reconstruction for accelerated relaxometry - Siemens Healthineers (Belgium) (pdf - 149 kB)
- DC3: Implementation of efficient simultaneous T2 and diffusion brain mapping - Instituto Superior Técnico (Portugal) (pdf - 145 kB)
- DC 4: Acquisition and joint reconstruction of dynamically weighted and undersampled MR-datasets - Bruker BioSpin (Germany) (pdf - 135 kB)
- DC 5: Robust DL Models for Accelerated Multi-Contrast MRI Reconstruction from Nonuniform k-space Data - Ghent University (Belgium) (pdf - 133 kB)
- DC 6: qMRI reconstruction with intra-scan motion compensation, uncertainty estimation, and segmentation - Erasmus MC (The Netherlands) (pdf - 130 kB)
- DC 7: Trustworthy AI for DL-based reconstruction of multi-parametric qMRI - Technische Universität München (Germany) (pdf - 176 kB)
- DC 8: Developing a Deep learning-based qMRI method for multi-TE arterial spin labelling MRI - University of Antwerp (Belgium) (pdf - 175 kB)
- DC 9: Unsupervised uncertainty prediction for trustworthy and unbiased qMRI - Helmholtz Munich (Germany) (pdf - 186 kB)
- DC 10: Develop a DL-based qMRI method for robust multi-compartment diffusion-relaxometry - Erasmus MC (The Netherlands) (pdf - 130 kB)
- DC 11: Multiparametric MRI with quantification of the brain clearance and iron content in the diseased brain - University of Antwerp (Belgium) (pdf - 147 kB)
- DC 12: Probing brain microstructure with multi-parametric, multi-component qMRI, AI at 3T and 7T - Forschungszentrum Jülich (Germany) (pdf - 141 kB)
- DC 13: Brain age estimation from multiparametric k-space data - Amsterdam UMC (The Netherlands) (pdf - 149 kB)
- DC 14: MRI image quality enhancement for quantitative applications - icometrix (Belgium) (pdf - 138 kB)
- DC 15: Quantifying neurofluid pathways through AI-accelerated long T1/T2-range MRI - Oslo University Hospital (Norway) (pdf - 144 kB)
- DC 16: Quantitative phenotyping via the generative modelling of quantitative MRI data - King's College London (United Kingdom) (pdf - 141 kB)
Overview of our PhD positions in the qMRI pipeline
