Proceedings II of the 28st Conference STUDENT EEICT 2022: Selected Papers. 2022
DOI: 10.13164/eeict.2022.271
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Unfolded Low-rank + Sparse Reconstruction for MRI

Abstract: 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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