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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 …
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 …
Joint cross-attention network with deep modality prior for fast MRI reconstruction
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 …
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
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 …
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 …
imaging. How to preserve the image details in reconstruction is always challenging. In this …
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 …
CloudBrain-ReconAI: An online platform for MRI reconstruction and image quality evaluation
Efficient collaboration between engineers and radiologists is important for image
reconstruction algorithm development and image quality evaluation in magnetic resonance …
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 …
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
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 …
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
Efficient collaboration between engineers and radiologists is important for image
reconstruction algorithm development and image quality evaluation in magnetic resonance …
reconstruction algorithm development and image quality evaluation in magnetic resonance …