One-dimensional deep low-rank and sparse network for accelerated MRI
Deep learning has shown astonishing performance in accelerated magnetic resonance
imaging (MRI). Most state-of-the-art deep learning reconstructions adopt the powerful …
imaging (MRI). Most state-of-the-art deep learning reconstructions adopt the powerful …
IMJENSE: scan-specific implicit representation for joint coil sensitivity and image estimation in parallel MRI
Parallel imaging is a commonly used technique to accelerate magnetic resonance imaging
(MRI) data acquisition. Mathematically, parallel MRI reconstruction can be formulated as an …
(MRI) data acquisition. Mathematically, parallel MRI reconstruction can be formulated as an …
Undersampled MRI reconstruction based on spectral graph wavelet transform
J Lang, C Zhang, D Zhu - Computers in Biology and Medicine, 2023 - Elsevier
Compressed sensing magnetic resonance imaging (CS-MRI) has exhibited great potential
to accelerate magnetic resonance imaging if an image can be sparsely represented. How to …
to accelerate magnetic resonance imaging if an image can be sparsely represented. How to …
One for multiple: Physics-informed synthetic data boosts generalizable deep learning for fast MRI reconstruction
Z Wang, X Yu, C Wang, W Chen, J Wang… - arXiv preprint arXiv …, 2023 - arxiv.org
Magnetic resonance imaging (MRI) is a widely used radiological modality renowned for its
radiation-free, comprehensive insights into the human body, facilitating medical diagnoses …
radiation-free, comprehensive insights into the human body, facilitating medical diagnoses …
A faithful deep sensitivity estimation for accelerated magnetic resonance imaging
Magnetic resonance imaging (MRI) is an essential diagnostic tool that suffers from
prolonged scan time. To alleviate this limitation, advanced fast MRI technology attracts …
prolonged scan time. To alleviate this limitation, advanced fast MRI technology attracts …
Fast and Calibrationless low-rank parallel imaging reconstruction through unrolled deep learning estimation of multi-channel spatial support maps
Low-rank technique has emerged as a powerful calibrationless alternative for parallel
magnetic resonance (MR) imaging. Calibrationless low-rank reconstruction, such as low …
magnetic resonance (MR) imaging. Calibrationless low-rank reconstruction, such as low …
Deep Separable Spatiotemporal Learning for Fast Dynamic Cardiac MRI
Dynamic magnetic resonance imaging (MRI) plays an indispensable role in cardiac
diagnosis. To enable fast imaging, the k-space data can be undersampled but the image …
diagnosis. To enable fast imaging, the k-space data can be undersampled but the image …
Structured Low-Rank Tensor Completion for IoT Spatiotemporal High-resolution Sensing Data Reconstruction
X Zhang, J He, XA Pan, Y Chi… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Due to various restrictions, some Internet of Things (IoT) sensing layers can only deploy a
small number of sensor nodes for spatiotemporal low-resolution environmental information …
small number of sensor nodes for spatiotemporal low-resolution environmental information …
Bloch equation enables physics-informed neural network in parametric magnetic resonance imaging
Magnetic resonance imaging (MRI) is an important non-invasive imaging method in clinical
diagnosis. Beyond the common image structures, parametric imaging can provide the …
diagnosis. Beyond the common image structures, parametric imaging can provide the …
Multi-contrast image super-resolution with deformable attention and neighborhood-based feature aggregation (DANCE): Applications in anatomic and metabolic MRI
W Chen, S Wu, S Wang, Z Li, J Yang, H Yao… - Medical Image …, 2025 - Elsevier
Multi-contrast magnetic resonance imaging (MRI) reflects information about human tissues
from different perspectives and has wide clinical applications. By utilizing the auxiliary …
from different perspectives and has wide clinical applications. By utilizing the auxiliary …