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Cited By

Validation and Generalizability of Self-Supervised Image Reconstruction
Methods for Undersampled MRI

v1v2v3 (latest)

Validation and Generalizability of Self-Supervised Image Reconstruction Methods for Undersampled MRI

Machine Learning for Biomedical Imaging (MLBI), 2022

29 January 2022

Meritxell Bach Cuadra

Erick Jorge Canales-Rodríguez

Jean-Philippe Thiran

ArXiv (abs)PDF HTML Github

Papers citing "Validation and Generalizability of Self-Supervised Image Reconstruction Methods for Undersampled MRI"

4 / 4 papers shown

Towards Architecture-Agnostic Untrained Network Priors for Image
Reconstruction with Frequency Regularization

Towards Architecture-Agnostic Untrained Network Priors for Image Reconstruction with Frequency RegularizationEuropean Conference on Computer Vision (ECCV), 2023

461

3

0

15 Dec 2023

To be or not to be stable, that is the question: understanding neural
networks for inverse problems

To be or not to be stable, that is the question: understanding neural networks for inverse problemsSIAM Journal on Scientific Computing (SISC), 2022

David Evangelista

E. L. Piccolomini

285

10

0

24 Nov 2022

NESTANets: Stable, accurate and efficient neural networks for
analysis-sparse inverse problems

NESTANets: Stable, accurate and efficient neural networks for analysis-sparse inverse problemsSampling Theory, Signal Processing, and Data Analysis (TSPDA), 2022

Maksym Neyra-Nesterenko

314

11

0

02 Mar 2022

The troublesome kernel -- On hallucinations, no free lunches and the
accuracy-stability trade-off in inverse problems

The troublesome kernel -- On hallucinations, no free lunches and the accuracy-stability trade-off in inverse problemsSIAM Review (SIAM Rev.), 2020

543

59

0

05 Jan 2020

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