Stephanie Hougen with Mark Griswold
Modeling Magnetic Resonance Fingerprinting Signals in the Presence of Exchange
Magnetic resonance imaging (MRI) has many applications in our current healthcare system. The MRI group at CWRU has recently introduced a new imaging technique, magnetic resonance fingerprinting (MRF), that presents a new quantitative approach to imaging. In current MRI techniques, it is assumed that each voxel only contains a single species of tissue, and thus has single component relaxation. The purpose of this project is to investigate situations when this assumption is not sufficient, and to see whether MRF can actually separate out the different components. I will be looking into the signal behavior that occurs when there is more than one substance in each voxel, and these substances are in exchange with one another. I will use MATLAB to implement specific models of different scanning situations. I will then compare these results with those obtained from real measurements. By removing the single component relaxation assumption, we believe that a more accurate result can be modeled by accounting for the exchange that occurs within each voxel.