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National Repository of Grey Literature 1 records found  Search took 0.00 seconds. 
Unfolded Low-rank + Sparse Reconstruction for MRI
 Mokrý, O. ; Vitouš, Jiří
We apply the methodology of deep unfolding on the problem of reconstruction of DCE-MRI data. The problem is formulated as a convex optimization problem, solvable via the primal-dual splitting algorithm. The unfolding allows for optimal hyperparameter selection for the model. We examine two approaches - with the parameters shared across the layers/iterations, and an adaptive version where the parameters can differ. The results demonstrate that the more complex model can better adapt to the data.
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