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Deep Learning COVID-19 Features on CXR Using Limited Training Data Sets

IEEE transactions on medical imaging, 2020-08, Vol.39 (8), p.2688-2700

2020

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A deep convolutional neural network using directional wavelets for low‐dose X‐ray CT reconstruction

Medical physics (Lancaster), 2017-10, Vol.44 (10), p.e360-e375

2017

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Image Reconstruction: From Sparsity to Data-Adaptive Methods and Machine Learning

Proceedings of the IEEE, 2020-01, Vol.108 (1), p.86-109

2020

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Statistical analysis of fNIRS data: A comprehensive review

NeuroImage (Orlando, Fla.), 2014-01, Vol.85, p.72-91

2014

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Deep Residual Learning for Accelerated MRI Using Magnitude and Phase Networks

IEEE transactions on biomedical engineering, 2018-09, Vol.65 (9), p.1985-1995

2018

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Deep Convolutional Framelet Denosing for Low-Dose CT via Wavelet Residual Network

IEEE transactions on medical imaging, 2018-06, Vol.37 (6), p.1358-1369

2018

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Sparse and Low-Rank Decomposition of a Hankel Structured Matrix for Impulse Noise Removal

IEEE transactions on image processing, 2018-03, Vol.27 (3), p.1448-1461

2018

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Bidirectional generation of structure and properties through a single molecular foundation model

Nature communications, 2024-03, Vol.15 (1), p.2323-2323

2024

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Projection reconstruction MR imaging using FOCUSS

Magnetic resonance in medicine, 2007-04, Vol.57 (4), p.764-775

2007

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Annihilating Filter-Based Low-Rank Hankel Matrix Approach for Image Inpainting

IEEE transactions on image processing, 2015-11, Vol.24 (11), p.3498-3511

2015

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Cycle‐consistent adversarial denoising network for multiphase coronary CT angiography

Medical physics (Lancaster), 2019-02, Vol.46 (2), p.550-562

2019

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Reference-free single-pass EPI Nyquist ghost correction using annihilating filter-based low rank Hankel matrix (ALOHA)

Magnetic resonance in medicine, 2016-12, Vol.76 (6), p.1775-1789

2016

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Deep residual learning for compressed sensing MRI

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), 2017, p.15-18

2017

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Compressed Sensing Shape Estimation of Star-Shaped Objects in Fourier Imaging

IEEE signal processing letters, 2007-10, Vol.14 (10), p.750-753

Ye, Jong Chul

2007

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Understanding Graph Isomorphism Network for rs-fMRI Functional Connectivity Analysis

Frontiers in neuroscience, 2020-06, Vol.14, p.630-630

2020

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A General Framework for Compressed Sensing and Parallel MRI Using Annihilating Filter Based Low-Rank Hankel Matrix

IEEE transactions on computational imaging, 2016-12, Vol.2 (4), p.480-495

2016

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Compressive MUSIC: Revisiting the Link Between Compressive Sensing and Array Signal Processing

IEEE transactions on information theory, 2012-01, Vol.58 (1), p.278-301

2012

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Sparse-View Spectral CT Reconstruction Using Spectral Patch-Based Low-Rank Penalty

IEEE transactions on medical imaging, 2015-03, Vol.34 (3), p.748-760

2015

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A Data-Driven Sparse GLM for fMRI Analysis Using Sparse Dictionary Learning With MDL Criterion

IEEE transactions on medical imaging, 2011-05, Vol.30 (5), p.1076-1089

2011

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Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

IEEE transactions on information theory, 2017-02, Vol.63 (2), p.777-801

2017

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Unpaired Training of Deep Learning tMRA for Flexible Spatio-Temporal Resolution

IEEE transactions on medical imaging, 2021-01, Vol.40 (1), p.166-179

2021

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Unpaired deep learning for pharmacokinetic parameter estimation from dynamic contrast-enhanced MRI without AIF measurements

NeuroImage (Orlando, Fla.), 2024-05, Vol.291, p.120571-120571, Article 120571

2024

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Motion Adaptive Patch-Based Low-Rank Approach for Compressed Sensing Cardiac Cine MRI

IEEE transactions on medical imaging, 2014-11, Vol.33 (11), p.2069-2085

2014

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Deep learning enables reference-free isotropic super-resolution for volumetric fluorescence microscopy

Nature communications, 2022-06, Vol.13 (1), p.3297-3297, Article 3297

2022

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FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data

Scientific reports, 2014-04, Vol.4 (1), p.4577-4577, Article 4577

2014

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Deep Learning COVID-19 Features on CXR Using Limited Training Data Sets

A deep convolutional neural network using directional wavelets for low‐dose X‐ray CT reconstruction

Image Reconstruction: From Sparsity to Data-Adaptive Methods and Machine Learning

Statistical analysis of fNIRS data: A comprehensive review

Deep Residual Learning for Accelerated MRI Using Magnitude and Phase Networks

Deep Convolutional Framelet Denosing for Low-Dose CT via Wavelet Residual Network

Sparse and Low-Rank Decomposition of a Hankel Structured Matrix for Impulse Noise Removal

Bidirectional generation of structure and properties through a single molecular foundation model

Projection reconstruction MR imaging using FOCUSS

Annihilating Filter-Based Low-Rank Hankel Matrix Approach for Image Inpainting

Cycle‐consistent adversarial denoising network for multiphase coronary CT angiography

Reference-free single-pass EPI Nyquist ghost correction using annihilating filter-based low rank Hankel matrix (ALOHA)

Deep residual learning for compressed sensing MRI

Compressed Sensing Shape Estimation of Star-Shaped Objects in Fourier Imaging

Understanding Graph Isomorphism Network for rs-fMRI Functional Connectivity Analysis

A General Framework for Compressed Sensing and Parallel MRI Using Annihilating Filter Based Low-Rank Hankel Matrix

Compressive MUSIC: Revisiting the Link Between Compressive Sensing and Array Signal Processing

Sparse-View Spectral CT Reconstruction Using Spectral Patch-Based Low-Rank Penalty

A Data-Driven Sparse GLM for fMRI Analysis Using Sparse Dictionary Learning With MDL Criterion

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

Unpaired Training of Deep Learning tMRA for Flexible Spatio-Temporal Resolution

Unpaired deep learning for pharmacokinetic parameter estimation from dynamic contrast-enhanced MRI without AIF measurements

Motion Adaptive Patch-Based Low-Rank Approach for Compressed Sensing Cardiac Cine MRI

Deep learning enables reference-free isotropic super-resolution for volumetric fluorescence microscopy

FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data

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