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Advancing MRI reconstruction: a systematic review of deep learning and compressed sensing integration
Magnetic resonance imaging (MRI) is a non-invasive imaging modality and provides
comprehensive anatomical and functional insights into the human body. However, its long …
comprehensive anatomical and functional insights into the human body. However, its long …
A review of deep learning-based reconstruction methods for accelerated MRI using spatiotemporal and multi-contrast redundancies
Accelerated magnetic resonance imaging (MRI) has played an essential role in reducing
data acquisition time for MRI. Acceleration can be achieved by acquiring fewer data points in …
data acquisition time for MRI. Acceleration can be achieved by acquiring fewer data points in …
IWNeXt: an image-wavelet domain ConvNeXt-based network for self-supervised multi-contrast MRI reconstruction
Y Yan, T Yang, C Jiao, A Yang… - Physics in Medicine & …, 2024 - iopscience.iop.org
Objective. Multi-contrast magnetic resonance imaging (MC MRI) can obtain more
comprehensive anatomical information of the same scanning object but requires a longer …
comprehensive anatomical information of the same scanning object but requires a longer …
Fast MRI reconstruction using deep learning-based compressed sensing: A systematic review
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 …
invasive and highly detailed look into the human body. However, the long acquisition times …
[HTML][HTML] Deep Learning-Assisted Automatic Diagnosis of Anterior Cruciate Ligament Tear in Knee Magnetic Resonance Images
X Wang, Y Wu, J Li, Y Li, S Xu - Tomography, 2024 - mdpi.com
Anterior cruciate ligament (ACL) tears are prevalent knee injures, particularly among active
individuals. Accurate and timely diagnosis is essential for determining the optimal treatment …
individuals. Accurate and timely diagnosis is essential for determining the optimal treatment …
A Learned Proximal Alternating Minimization Algorithm and Its Induced Network for a Class of Two-block Nonconvex and Nonsmooth Optimization
Y Chen, L Liu, L Zhang - arxiv preprint arxiv:2411.06333, 2024 - arxiv.org
This work proposes a general learned proximal alternating minimization algorithm, LPAM,
for solving learnable two-block nonsmooth and nonconvex optimization problems. We tackle …
for solving learnable two-block nonsmooth and nonconvex optimization problems. We tackle …
Frequency Domain-based Matching and Integration Network for Multi-contrast MRI Reconstruction
L Wang, X Zhang, D **ong… - … Conference on Image …, 2023 - ieeexplore.ieee.org
Multi-contrast magnetic resonance (MR) images are crucial for diagnosing diseases and
analysis in clinical practice, yet their acquisition often entails long scanning procedures …
analysis in clinical practice, yet their acquisition often entails long scanning procedures …