Keywords: Image Reconstruction, Image Reconstruction
Motivation: Dictionary matching, used extensively in quantitative MRI, is resistant to standard approaches to spatial regularisation due to its discrete nature.
Goal(s): Demonstrate the feasibilty of efficient spatial regularisation of parameter maps produced via dictionary matching, in this work using total variation (TV) regularisation.
Approach: Spatially regularised dictionary matching was formulated as an optimisation on a discrete Markov random field, and the result optimisation problem solved using a primal-dual strategy, with the efficient iterative solver FastPD.
Results: TV regularisation improved apparent quality of parameter maps in phantoms and in vivo.
Impact: The proposed technique offers a means to improve the quality of parameter maps from any quantitative framework employing dictionary matching, covering a wide range of possible anatomies and clinical applications.
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