Dictionary and model-based methods in quantitative MRI reconstruction

Monday, October 14, 2019 - 2:55pm - 3:45pm
Keller 3-180
Mariya Doneva (Philips Research Laboratory)
This lecture gives an overview of methods for scan time reduction in quantitative MRI based on regularized image reconstruction. Besides the generic constraints that can be used for image series, the known signal model in quantitative MRI permits designing a model-based constraint tailored to the specific application. This is a much stronger prior knowledge, which, provided that the model is accurate, enables even higher accelerations and improved image quality. As a special class of model-based reconstruction, dictionary based methods are considered, which replace the inversion of a non-linear signal model with a search in a so-called dictionary. The dictionary is usually generated in a way to provide a sparse representation of the measured signal evolution in the parametric direction and applied in a sparsity constrained reconstruction.
The main concepts are explained for the example of relaxation parameter mapping. A brief overview of additional methods for efficient quantitative MRI is given, and the relation to the novel approach for quantitative MRI coined MR Fingerprinting is explained.