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Adversarial Robustness of MR Image Reconstruction under Realistic
  Perturbations

Adversarial Robustness of MR Image Reconstruction under Realistic Perturbations

5 August 2022
Jan Nikolas Morshuis
S. Gatidis
Matthias Hein
Christian F. Baumgartner
    AAMLOOD
ArXiv (abs)PDFHTML

Papers citing "Adversarial Robustness of MR Image Reconstruction under Realistic Perturbations"

8 / 8 papers shown
Title
NPB-REC: A Non-parametric Bayesian Deep-learning Approach for
  Undersampled MRI Reconstruction with Uncertainty Estimation
NPB-REC: A Non-parametric Bayesian Deep-learning Approach for Undersampled MRI Reconstruction with Uncertainty Estimation
Samah Khawaled
Moti Freiman
UQCV
64
3
0
06 Apr 2024
Robustness and Exploration of Variational and Machine Learning
  Approaches to Inverse Problems: An Overview
Robustness and Exploration of Variational and Machine Learning Approaches to Inverse Problems: An Overview
Alexander Auras
Kanchana Vaishnavi Gandikota
Hannah Droege
Michael Moeller
AAML
74
0
0
19 Feb 2024
Evaluating Adversarial Robustness of Low dose CT Recovery
Evaluating Adversarial Robustness of Low dose CT Recovery
Kanchana Vaishnavi Gandikota
Paramanand Chandramouli
Hannah Dröge
Michael Moeller
OODAAML
60
3
0
18 Feb 2024
Uncertainty Estimation and Propagation in Accelerated MRI Reconstruction
Uncertainty Estimation and Propagation in Accelerated MRI Reconstruction
Paul Fischer
Thomas Kustner
Christian F. Baumgartner
94
8
0
04 Aug 2023
Adversarial Attack and Defense for Medical Image Analysis: Methods and
  Applications
Adversarial Attack and Defense for Medical Image Analysis: Methods and Applications
Junhao Dong
Junxi Chen
Xiaohua Xie
Jianhuang Lai
Hechang Chen
AAMLMedIm
129
19
0
24 Mar 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 problems
David Evangelista
J. Nagy
E. Morotti
E. L. Piccolomini
76
5
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 problems
Maksym Neyra-Nesterenko
Ben Adcock
75
9
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 problems
N. Gottschling
Vegard Antun
A. Hansen
Ben Adcock
87
35
0
05 Jan 2020
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