Keywords
Research Disciplines
The Carinthian University of Applied Sciences and the Medical University of Vienna have established a cooperation, supported by the Austrian Science Fund FWF, in order to sustainably interlink basic university research and applied brain research. In the course of this project, seven PhD positions will be opened to develop new methods in the field of ultra-high field magnetic resonance imaging, histology, and artificial intelligence. The research aims to make developments and standards in the treatment of brain tumors and demyelinating diseases such as multiple sclerosis. An innovative research platform is being established to pool scientific knowledge. It combines scientific expertise and equipment at the cutting edge of technology from three departments of the Medical University of Vienna - the department of Radiology and Nuclear Medicine, the department of Neurology, and the department of Neurosurgery - and the University of Applied Sciences Carinthia - department of Engineering & IT and Medical Engineering and Analytics. The goal of this cooperative doctoral program is, among other things, the establishment of new clinically relevant biomarkers in neurological diseases through the development of innovative MR imaging techniques. These technologies will be used in the future as analysis and visualization tools with high clinical impact. The collaboration between the Carinthia University of Applied Sciences and the Medical University of Vienna should also lead to the training of the next generation of scientists, developers, and physicians who can jointly use these technologies in clinical routine. An example of this would be the optimization of neurosurgical planning for a better determination of the type of tumor, its environment, and the simulation of the intervention with the help of virtual reality. In order to meet the highest international standards, the PhD program includes at least one stay abroad per PhD student with international research partners. Seven internationally renowned cooperation partners from academia (e.g. Harvard and MIT) and industry (e.g. ICOMETRIX) have agreed to host our candidates. In addition to the positive effects for all stakeholders involved in this project, this interdisciplinary and cooperative PhD program will also significantly increase the amount of medical research in Carinthia by incorporating the latest findings from the largest medical research institution in Austria.
| Title | Year(s) | DOI / Link |
|---|---|---|
| Preoperative prediction of 5-ALA fluorescence in gliomas: comparison of 7-Tesla magnetic resonance spectroscopic imaging, contrast-enhancement on MRI, and positron emission tomography.European radiology | 2026 | 10.1007/s00330-026-12430-w |
| Topographical mapping of metabolic abnormalities in multiple sclerosis using rapid echo-less 3D-MR spectroscopic imaging at 7T |
No additional funding sources recorded.
Research Fields
| 2025 |
| 10.1016/j.neuroimage.2025.12… |
| Synthesized myelin and iron stainings from 7T multi-contrast MRI via deep learningNeuroImage | 2025 | 10.1016/j.neuroimage.2025.12… |
| Correcting motion-related B0 inhomogeneities in magnetic resonance imaging via combined spherical harmonics and AC/DC matrix coils using DL-based prediction-simulation study.Scientific reports | 2026 | 10.1038/s41598-026-56900-z |
| High-Resolution Mapping of Tumor and Peritumoral Glutamate and Glutamine in Gliomas Using 7-T MRSIRadiology: Imaging Cancer | 2025 | 10.1148/rycan.240494 |
| Towards ihMT Imaging at 7T Using 3D Centric Gradient Echo Readout for ihMT Contrast Optimization: Preliminary Results | 2025 | Link |
| 7T 3D-MR Spectroscopic Imaging of Glutathione Uncovers Oxidative Stress Signatures in Multiple Sclerosis Patients | 2025 | — |
| Prediction of myelin stainings using 7T MRI and deep learning | 2024 | Link |
| Using Deep Learning and 7T MRI to Predict Myelin Stainings Histology | 2025 | — |
| Correlations between 5-ALA fluorescence and 7T MRSI in gliomas: Preliminary observations | 2024 | — |
| Linewidth Analysis of MR Spectrum in AI-Based Dynamic Shimming in the Presence of Motion | 2025 | Link |
| 7T 3D-MR Spectroscopic Imaging Reveals Tissue- and Lesion-Specific Oxidative Stress in Multiple Sclerosis | 2025 | Link |
| Using Deep Learning to Predict Myelin Staining Patterns from 7T MRI | 2024 | Link |
| Correcting motion-related B0 Inhomogeneities via Combined Spherical Harmonics and AC/DCMatrix Coils Using AI-based Prediction | 2025 | Link |
| Imaging-based prediction of 5-ALA fluorescence in gliomas using preoperative 7T MRSI compared to T1w MRI and PET | 2025 | — |
| Interactive Visualization for Optimized Preoperative Neurosurgical Planning | 2025 | Link |
| Utilizing 7T MRI and Deep Learning for the Prediction of Myelin Stainings | 2024 | — |
| Correlations between 5-ALA fluorescence and 7T MRSI ratios in gliomas: Preliminary results | 2024 | — |
| Synthesized Histology Images of Myelin and Iron Stainings from 7T Multi-Contrast MRI | 2024 | Link |
| 7T MRI-Synthesized Iron and Myelin Histology by Deep Learning | 2025 | Link |
| Correcting motion related B0 Inhomogeneities Using AI based Prediction | 2025 | — |
| 7T 3D-MR Spectroscopic Imaging of GSH and GPX4 Immunohistochemistry Staining Reveal Oxidative Stress Patterns in MS Lesions | 2025 | Link |
| Preoperative Glioma Characterization: Predicting 5-ALA Fluorescence Using 7T MRSI, Contrast MRI, and PET Imaging | 2025 | — |
| Lesion-Level Glutathione Mapping Reveals Oxidative Stress Patterns in Patients with Multiple Sclerosis Using 7T 3D FID MRSI | 2025 | — |