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Simulation of Phase-Contrast MRI
The aim of this project is to develop a PC-MRI simulation framework to investigate various MR parameters and their impact on the quality of the generated synthetic images.
Phase-contrast magnetic resonance imaging (PC-MRI) is an imaging technique that allows to measure time-resolved volumetric flow patterns (4D flow). In particular, the ability to measure velocity and turbulence in the aorta, makes 4D flow MRI very promising for future assessment of aortic pathologies in a clinical framework. Turbulence has been associated with increased wall shear stresses (WSS) and pressure drop, both strongly linked to a variety of aortic pathologies. Accurate measurement of turbulence is fundamental in order to efficiently implement new medical imaging procedures. In order to better understand and predict 4D flow MRI, a simulation framework is a must.
Phase-contrast magnetic resonance imaging (PC-MRI) is an imaging technique that allows to measure time-resolved volumetric flow patterns (4D flow). In particular, the ability to measure velocity and turbulence in the aorta, makes 4D flow MRI very promising for future assessment of aortic pathologies in a clinical framework. Turbulence has been associated with increased wall shear stresses (WSS) and pressure drop, both strongly linked to a variety of aortic pathologies. Accurate measurement of turbulence is fundamental in order to efficiently implement new medical imaging procedures. In order to better understand and predict 4D flow MRI, a simulation framework is a must.
Our investigation has multiple objectives and can accommodate for the student’s interests. Please contact us if you are interested and would like to know more. Potential tasks include:
- Computational fluid dynamics of idealized stenotic geometries or/and patient specific geometries
- Particle-tracking and generation of turbulent pathlines
- Development of a PC-MRI simulation tool
- Analysis and comparison of CFD results vs simulated PC-MRI results
**Requisites** Knowledge in a coding language (Python preferred). Knowledge in CFD is a plus. Knowledge of basic imaging principles for MRI is a plus.
Our investigation has multiple objectives and can accommodate for the student’s interests. Please contact us if you are interested and would like to know more. Potential tasks include:
- Computational fluid dynamics of idealized stenotic geometries or/and patient specific geometries
- Particle-tracking and generation of turbulent pathlines
- Development of a PC-MRI simulation tool
- Analysis and comparison of CFD results vs simulated PC-MRI results
**Requisites** Knowledge in a coding language (Python preferred). Knowledge in CFD is a plus. Knowledge of basic imaging principles for MRI is a plus.
Please contact Pietro Dirix (dirix@biomed.ee.ethz.ch) or Charles McGrath (mcgrath@biomed.ee.ethz.ch) if you are interested in the topic. The project’s focuses can be adjusted to the student’s interest and experience. Interested students are asked to send a CV and a transcript of records of the Masters. Supervising professor: Sebastian Kozerke (kozerke@biomed.ee.ethz.ch)
Please contact Pietro Dirix (dirix@biomed.ee.ethz.ch) or Charles McGrath (mcgrath@biomed.ee.ethz.ch) if you are interested in the topic. The project’s focuses can be adjusted to the student’s interest and experience. Interested students are asked to send a CV and a transcript of records of the Masters. Supervising professor: Sebastian Kozerke (kozerke@biomed.ee.ethz.ch)