Denoising Generalized Expectation-Consistent Approximation for MR Image Recovery-Reference-Cited by-同舟云学术

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Denoising Generalized Expectation-Consistent Approximation for MR Image Recovery

Published:2022-09 Issue:3 Volume:3 Page:528-542
ISSN:2641-8770
Container-title:IEEE Journal on Selected Areas in Information Theory
language:
Short-container-title:IEEE J. Sel. Areas Inf. Theory

Author:

Shastri Saurav K.¹^ORCID,Ahmad Rizwan²,Metzler Christopher A.³^ORCID,Schniter Philip¹^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH, USA

2. Department of Biomedical Engineering, The Ohio State University, Columbus, OH, USA

3. Department of Computer Science, The University of Maryland, College Park, MD, USA

Funder

National Institutes of Health

National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Medicine

Link

https://ieeexplore.ieee.org/ielam/8700143/10077203/9893363-aam.pdf

Reference79 articles.

1. DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction

2. Rigorous dynamics of expectation-propagation-based signal recovery from unitarily invariant measurements

3. Deep Convolutional Neural Network for Inverse Problems in Imaging

4. Plug-in estimation in high-dimensional linear inverse problems: A rigorous analysis;fletcher;Proc Neural Inf Process Syst Conf,2018

5. Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing

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1. Deep Unfolding Network for ISAR Imaging Based on Hypernetwork;IEEE Transactions on Aerospace and Electronic Systems;2023-12

2. Deep Expectation-Consistent Approximation for Phase Retrieval;2023 57th Asilomar Conference on Signals, Systems, and Computers;2023-10-29

3. On The Stability of Approximate Message Passing with Independent Measurement Ensembles;2023 IEEE International Symposium on Information Theory (ISIT);2023-06-25

4. Improved Sparse Signal Recovery via Adaptive Correlated Noise Model;IEEE Transactions on Computational Imaging;2022

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