Job Offer from April 24, 2023
The Max Planck Institute for Biological Cybernetics Tuebingen has one of the most powerful magnetic resonance tomographs in the world, with a field strength of 9.4 Tesla. We are developing the technologies to use this device in basic research for non-invasive imaging of the central nervous system with very high spatial and temporal resolution. A major difficulty here is homogeneous signal excitation, as RF pulse interference can occur due to the higher sense frequency. To minimize resulting image artifacts, the 9.4 T MRI is equipped with 16 independent transmit channels (parallel transmit, pTX).
For the optimization of spatially selective pTX excitation pulses for high-resolution imaging of vessels in the human brain we are looking for a motivated HiWi, Bachelor or Master student.
Project overview:
Problem: Transmit field inhomogeneities (Figure 1) can lead to different inflow signal weightings in time of flight images + spatially varying signal to noise ratio (Figure 2).
Solution: pTX 'spoke' pulses for homogeneous slab selective excitation
Instead of one RF-pulse, use multiple sub-pulses with gradient blips in between (Figure 3)
Instead of a single scaling factor (conventional MRI), each RF pulse has a set of complex scaling weights (16 transmit channels, "parallel Transmit")
Project organization:
Step 1:
- optimize spokes pulses
- Existing simulation framework
- Based on slice orientation and position, calculate RF-magnitudes, RF-phases and gradient moments
Step 2:
- train neural network
- Input: slice position (fixed orientation and thickness)
- Self-supervised learning?
Step 3:
- Integrate into MR-sequence for online spokes design
Step 4:
- Implement for arbitrary slice orientation, thickness and positioning
Required Skills:
- Python programming
- basic understanding of machine learning techniques
- interest in medical imaging technology and physics
- reliability
Do not hesitate to contact us if you are interested:
Max-Planck-Ring 11
Dr. Jonas Bause
jonas.bause@tuebingen.mpg.de