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