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Navigator Design for Motion Tracking in Magnetic Resonance Imaging
Patient motion is one of the leading causes of image artifacts in MR imaging. The aim is to develop motion estimation techniques based on additional MR signals that allow compensating for patient motion in an online fashion. The navigated approach is particularly promising, because it is purely based on MR signals and does not require any additional hardware.
Keywords: MRI, Magnetic Resonance Imaging, Motion Correction, Online Control, Navigator Design, Signal Encoding
In this project, navigator signals are acquired along with the actual imaging scan to extract additional information for motion correction. The acquired navigator signals are evaluated by a motion estimation algorithm to update the scan geometry settings online. Herein, the navigator design, defined by its k-space trajectory, is particularly relevant for its capability to extract motion-related information. The goal of this project is to study how the choice of this trajectory design influences the accuracy and precision of our existing motion estimation algorithm. This can be done – depending on your interest and experience – with a combination of theoretical considerations, simulation studies and experiments at our MRI scanners.
For this project, you should have some programming experience with a scientific computing programming language/framework (e.g. Matlab or Python with Numpy/Scipy). Prior knowledge about magnetic resonance imaging (e.g. from the Magnetic Resonance in Medicine course) is a big plus.
In this project, navigator signals are acquired along with the actual imaging scan to extract additional information for motion correction. The acquired navigator signals are evaluated by a motion estimation algorithm to update the scan geometry settings online. Herein, the navigator design, defined by its k-space trajectory, is particularly relevant for its capability to extract motion-related information. The goal of this project is to study how the choice of this trajectory design influences the accuracy and precision of our existing motion estimation algorithm. This can be done – depending on your interest and experience – with a combination of theoretical considerations, simulation studies and experiments at our MRI scanners.
For this project, you should have some programming experience with a scientific computing programming language/framework (e.g. Matlab or Python with Numpy/Scipy). Prior knowledge about magnetic resonance imaging (e.g. from the Magnetic Resonance in Medicine course) is a big plus.
Not specified
Please contact Thomas Ulrich (ulrich@biomed.ee.ethz.ch) or Dr. Malte Riedel (riedel@biomed.ee.ethz.ch) if you are interested in hearing more about this topic and the different projects we can offer.
Please contact Thomas Ulrich (ulrich@biomed.ee.ethz.ch) or Dr. Malte Riedel (riedel@biomed.ee.ethz.ch) if you are interested in hearing more about this topic and the different projects we can offer.