Original title: Unfolded Low-rank + Sparse Reconstruction for MRI
Authors: Mokrý, Ondřej ; Vitouš, Jiří
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
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.
Keywords: DCE-MRI, proximal splitting algorithms, deep unfolding, L+S model
Host item entry: Proceedings II of the 28st Conference STUDENT EEICT 2022: Selected papers, ISBN 978-80-214-6030-0

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/208650

Permalink: http://www.nusl.cz/ntk/nusl-511919


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