IMJENSE: scan-specific implicit representation for joint coil sensitivity and image estimation in parallel MRI

R Feng, Q Wu, J Feng, H She, C Liu… - … on Medical Imaging, 2023 - ieeexplore.ieee.org
Parallel imaging is a commonly used technique to accelerate magnetic resonance imaging
(MRI) data acquisition. Mathematically, parallel MRI reconstruction can be formulated as an …

Advancing MRI reconstruction: a systematic review of deep learning and compressed sensing integration

M Safari, Z Eidex, CW Chang, RLJ Qiu… - arxiv preprint arxiv …, 2025 - arxiv.org
Magnetic resonance imaging (MRI) is a non-invasive imaging modality and provides
comprehensive anatomical and functional insights into the human body. However, its long …

Joint cross-attention network with deep modality prior for fast MRI reconstruction

K Sun, Q Wang, D Shen - IEEE Transactions on Medical …, 2023 - ieeexplore.ieee.org
Current deep learning-based reconstruction models for accelerated multi-coil magnetic
resonance imaging (MRI) mainly focus on subsampled k-space data of single modality using …

Fast MRI reconstruction using deep learning-based compressed sensing: A systematic review

M Safari, Z Eidex, CW Chang, RLJ Qiu, X Yang - Ar**v, 2024 - pmc.ncbi.nlm.nih.gov
Magnetic resonance imaging (MRI) has revolutionized medical imaging, providing a non-
invasive and highly detailed look into the human body. However, the long acquisition times …

Radial magnetic resonance image reconstruction with a deep unrolled projected fast iterative soft-thresholding network

B Qu, J Zhang, T Kang, J Lin, M Lin, H She… - Computers in Biology …, 2024 - Elsevier
Radially sampling of magnetic resonance imaging (MRI) is an effective way to accelerate the
imaging. How to preserve the image details in reconstruction is always challenging. In this …

Deep separable spatiotemporal learning for fast dynamic cardiac MRI

Z Wang, M **ao, Y Zhou, C Wang, N Wu, Y Li… - arxiv preprint arxiv …, 2024 - arxiv.org
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 …

CloudBrain-ReconAI: An online platform for MRI reconstruction and image quality evaluation

Y Zhou, C Qian, J Li, Z Wang, Y Hu, B Qu, L Zhu… - arxiv preprint arxiv …, 2022 - arxiv.org
Efficient collaboration between engineers and radiologists is important for image
reconstruction algorithm development and image quality evaluation in magnetic resonance …

MRI reconstruction with enhanced self-similarity using graph convolutional network

Q Ma, Z Lai, Z Wang, Y Qiu, H Zhang, X Qu - BMC Medical Imaging, 2024 - Springer
Abstract Background Recent Convolutional Neural Networks (CNNs) perform low-error
reconstruction in fast Magnetic Resonance Imaging (MRI). Most of them convolve the image …

Joint coil sensitivity and motion correction in parallel MRI with a self-calibrating score-based diffusion model

L Chen, X Tian, J Wu, R Feng, G Lao, Y Zhang… - Medical Image …, 2025 - Elsevier
Abstract Magnetic Resonance Imaging (MRI) stands as a powerful modality in clinical
diagnosis. However, it faces challenges such as long acquisition time and vulnerability to …

CloudBrain-ReconAI: A Cloud Computing Platform for MRI Reconstruction and Radiologists' Image Quality Evaluation

Y Zhou, C Qian, J Li, Z Wang, Y Hu… - … on Cloud Computing, 2024 - ieeexplore.ieee.org
Efficient collaboration between engineers and radiologists is important for image
reconstruction algorithm development and image quality evaluation in magnetic resonance …