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09/13/2023
A plug-and-play synthetic data deep learning for undersampled magnetic resonance image reconstruction
Magnetic resonance imaging (MRI) plays an important role in modern medic...
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09/12/2023
CloudBrain-NMR: An Intelligent Cloud Computing Platform for NMR Spectroscopy Processing, Reconstruction and Analysis
Nuclear Magnetic Resonance (NMR) spectroscopy has served as a powerful a...
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07/25/2023
One for Multiple: Physics-informed Synthetic Data Boosts Generalizable Deep Learning for Fast MRI Reconstruction
Magnetic resonance imaging (MRI) is a principal radiological modality th...
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06/16/2023
Magnetic Resonance Spectroscopy Quantification Aided by Deep Estimations of Imperfection Factors and Overall Macromolecular Signal
Magnetic Resonance Spectroscopy (MRS) is an important non-invasive techn...
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04/14/2023
Convex Dual Theory Analysis of Two-Layer Convolutional Neural Networks with Soft-Thresholding
Soft-thresholding has been widely used in neural networks. Its basic net...
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03/07/2023
Investigating and modeling day-to-day route choices based on laboratory experiments. Part II: A route-dependent attraction-based stochastic process model
To explain day-to-day (DTD) route-choice behaviors and traffic dynamics ...
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03/07/2023
Investigating day-to-day route choices based on multi-scenario laboratory experiments. Part I: Route-dependent attraction and its modeling
In the area of urban transportation networks, a growing number of day-to...
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12/29/2022
A Dynamics Theory of Implicit Regularization in Deep Low-Rank Matrix Factorization
Implicit regularization is an important way to interpret neural networks...
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10/23/2022
A Faithful Deep Sensitivity Estimation for Accelerated Magnetic Resonance Imaging
Recent deep learning is superior in providing high-quality images and ul...
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10/20/2022
Physics-informed deep diffusion MRI reconstruction: break the bottleneck of training data in artificial intelligence
In this work, we propose a Physics-Informed Deep Diffusion magnetic reso...
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03/21/2022
Physics-driven Synthetic Data Learning for Biomedical Magnetic Resonance
Deep learning has innovated the field of computational imaging. One of i...
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12/09/2021
One-dimensional Deep Low-rank and Sparse Network for Accelerated MRI
Deep learning has shown astonishing performance in accelerated magnetic ...
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01/26/2021
Denoising Single Voxel Magnetic Resonance Spectroscopy with Deep Learning on Repeatedly Sampled In Vivo Data
Objective: Magnetic Resonance Spectroscopy (MRS) is a noninvasive tool t...
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12/29/2020
Accelerated NMR Spectroscopy: Merge Optimization with Deep Learning
Multi-dimensional NMR spectroscopy is an invaluable biophysical tool in ...
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11/13/2020
TLab: Traffic Map Movie Forecasting Based on HR-NET
The problem of the effective prediction for large-scale spatio-temporal ...
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01/30/2020
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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01/13/2020
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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09/24/2019
pISTA-SENSE-ResNet for Parallel MRI Reconstruction
Magnetic resonance imaging has been widely applied in clinical diagnosis...
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09/17/2019
A Convergence Proof of Projected Fast Iterative Soft-thresholding Algorithm for Parallel Magnetic Resonance Imaging
The boom of non-uniform sampling and compressed sensing techniques drama...
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04/09/2019
Accelerated Nuclear Magnetic Resonance Spectroscopy with Deep Learning
Nuclear magnetic resonance (NMR) spectroscopy serves as an indispensable...
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04/06/2016
Hankel Matrix Nuclear Norm Regularized Tensor Completion for N-dimensional Exponential Signals
Signals are generally modeled as a superposition of exponential function...
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04/29/2015
Projected Iterative Soft-thresholding Algorithm for Tight Frames in Compressed Sensing Magnetic Resonance Imaging
Compressed sensing has shown great potentials in accelerating magnetic r...
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03/10/2015
Fast Multi-class Dictionaries Learning with Geometrical Directions in MRI Reconstruction
Objective: Improve the reconstructed image with fast and multi-class dic...
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03/10/2015
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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01/23/2013
