Department of Radiology - Medical Physics

The Department of Radiology, Medical Physics, is looking for a Master's Student in Physics for a research project on

Quantification of oxygen metabolism in human brain with oxygen-17 magnetic resonance imaging

Magnetic resonance imaging (MRI) is a powerful medical imaging technique for non-invasive investigation of the human body. In particular, ¹⁷O MRI allows direct quantification the oxygen metabolism in human brain. Over recent years we have established ¹⁷O MRI technologies on our new 3 Tesla MRI system. For this, we have developed specific radio frequency coils for ¹⁷O signal reception, MR control software (sequences) for the MRI system to acquire the ¹⁷O data, and image processing tools in combination with pharmacokinetic modelling of the signal dynamics.

In this master's project, we will first apply ¹⁷O MRI to the human brain. For this, the acquisition strategy will be refined, and a reconstruction pipeline will be created. The technology will then be further expanded for use in the kidneys for ex vivo organ testing to improve the outcome of kidney trans­plan­tations.

For this project, we are looking for a master's student candidate with the following profile:

• interest in medical physics and technology
• very good to excellent grades in Bachelor's and Master's courses
• programming experience (preferably in C++)
• self-responsibility and team orientation

The starting date is negotiable. Please submit your application and documents by email to:

^{Posted: January 10, 2018}

The Cardio-MRI group at the department of Radiology – Medical Physics, University Medical Center Freiburg, is currently looking for Master students (physics) for two research projects on

Efficient Sampling Strategies for High-resolution Dark-Blood SPACE MRI

Magnetic resonance imaging (MRI) provides an excellent soft tissue contrast and is therefore an indispensable tool in diagnostic imaging. With modern MRI scanners, high-resolution imaging (spatial resolution << 1 mm) becomes feasible which for example enables imaging of thin structures such as the wall of blood vessels. 3D vessel wall imaging is typically performed with so-called turbo spin echo (SPACE) sequences which provide a contrast behavior (dark-blood) that allows for clear delineation of the vessel wall. However, such MRI sequences still exhibit long measurements. The goal of this master’s project is to investigate novel sampling strategies for an efficient data sampling process, so that the overall acquisition process is shortened while image quality is maintained. The project is embedded within DFG-funded collaborations on vessel wall imaging in the brain and the carotid arteries.

                                                                AND

Improved MRI-based Flow Measurements via Adaptive VENC Selection

Besides its excellent capabilities for anatomic information, MRI also enables measurements of quantitative parameters such as velocity. These techniques are for example used for time-resolved 3D measurements of blood flow in the aorta or other structures. The sensitivity of such measurements mainly depends on the so-called VENC (velocity encoding) parameter. Common techniques use a single, fixed VENC value to measure the different flow velocities which occur over the course of the cardiac cycle. In this project, we want to develop improved techniques for MRI-based velocity measure-ments which use an adaptive selection of the VENC parameter to optimize the VENC according to the expected velocities. The project is part of a DFG-funded collaboration with partners from engineering and numerical computing at TU Darmstadt.

^{Posted: November 16, 2018}