Compressed sensing magnetic resonance imaging based on shearlet sparsity and nonlocal total variation
Author:
Affiliation:
1. University of Nevada, Electrical and Computer Engineering Department, Las Vegas, Nevada, United States
Publisher
SPIE-Intl Soc Optical Eng
Subject
Radiology Nuclear Medicine and imaging
Reference46 articles.
1. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
2. Compressed sensing
3. Communications on Pure and Applied Mathematics
4. Magnetic Resonance in Medicine
5. Compressed Sensing MRI
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2. Compressive Sensing MRI Reconstruction with Shearlet Sparsity and non-Convex Hybrid Total Variation;Applied Magnetic Resonance;2022-09-03
3. Discrete Shearlets as a Sparsifying Transform in Low-Rank Plus Sparse Decomposition for Undersampled (k, t)-Space MR Data;Journal of Imaging;2022-01-29
4. Tangent vector-based gradient method with l12-regularization: Iterative half thresholding algorithm for CS-MRI;Journal of Magnetic Resonance;2021-12
5. Multiscale wavelet-based regularized reconstruction algorithm for three-dimensional compressed sensing magnetic resonance imaging;Signal, Image and Video Processing;2021-03-28
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