Detail publikačního výsledku

Unfolded Low-rank + Sparse Reconstruction for MRI

MOKRÝ, O.; VITOUŠ, J.

Originální název

Unfolded Low-rank + Sparse Reconstruction for MRI

Anglický název

Unfolded Low-rank + Sparse Reconstruction for MRI

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

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.

Anglický abstrakt

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.

Klíčová slova

DCE-MRI, proximal splitting algorithms, deep unfolding, L+S model

Klíčová slova v angličtině

DCE-MRI, proximal splitting algorithms, deep unfolding, L+S model

Autoři

MOKRÝ, O.; VITOUŠ, J.

Rok RIV

2022

Vydáno

26.04.2022

Nakladatel

Brno University of Technology, Faculty of Electrical Engineering and Communication

Místo

Brno

ISBN

978-80-214-6030-0

Kniha

Proceedings II of the 28th Conference STUDENT EEICT 2022 Selected papers

Edice

1

Strany od

271

Strany do

275

Strany počet

5

URL

https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2022_sbornik_2_v3.pdf

BibTex

@inproceedings{BUT177793,
  author="Ondřej {Mokrý} and Jiří {Vitouš}",
  title="Unfolded Low-rank + Sparse Reconstruction for MRI",
  booktitle="Proceedings II of the 28th Conference STUDENT EEICT 2022 Selected papers",
  year="2022",
  series="1",
  pages="271--275",
  publisher="Brno University of Technology, Faculty of Electrical Engineering and Communication",
  address="Brno",
  isbn="978-80-214-6030-0",
  url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2022_sbornik_2_v3.pdf"
}