
A Convergence Proof of Projected Fast Iterative Softthresholding Algorithm for Parallel Magnetic Resonance Imaging
The boom of nonuniform sampling and compressed sensing techniques drama...
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Hankel Matrix Nuclear Norm Regularized Tensor Completion for Ndimensional Exponential Signals
Signals are generally modeled as a superposition of exponential function...
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Robust recovery of complex exponential signals from random Gaussian projections via low rank Hankel matrix reconstruction
This paper explores robust recovery of a superposition of R distinct com...
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Projected Iterative Softthresholding Algorithm for Tight Frames in Compressed Sensing Magnetic Resonance Imaging
Compressed sensing has shown great potentials in accelerating magnetic r...
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Fast Multiclass Dictionaries Learning with Geometrical Directions in MRI Reconstruction
Objective: Improve the reconstructed image with fast and multiclass dic...
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Spread spectrum compressed sensing MRI using chirp radio frequency pulses
Compressed sensing has shown great potential in reducing data acquisitio...
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Accelerated Nuclear Magnetic Resonance Spectroscopy with Deep Learning
Nuclear magnetic resonance (NMR) spectroscopy serves as an indispensable...
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pISTASENSEResNet for Parallel MRI Reconstruction
Magnetic resonance imaging has been widely applied in clinical diagnosis...
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Review and Prospect: Deep Learning in Nuclear Magnetic Resonance Spectroscopy
Since the concept of deep learning (DL) was formally proposed in 2006, i...
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Gaussian noise removal with exponential functions and spectral norm of weighted Hankel matrices
Exponential functions are powerful tools to model signals in various sce...
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