A review on deep learning MRI reconstruction without fully sampled k-space
Background Magnetic resonance imaging (MRI) is an effective auxiliary diagnostic method
in clinical medicine, but it has always suffered from the problem of long acquisition time …
in clinical medicine, but it has always suffered from the problem of long acquisition time …
Unsupervised MRI reconstruction via zero-shot learned adversarial transformers
Supervised reconstruction models are characteristically trained on matched pairs of
undersampled and fully-sampled data to capture an MRI prior, along with supervision …
undersampled and fully-sampled data to capture an MRI prior, along with supervision …
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 …
Dense recurrent neural networks for accelerated MRI: History-cognizant unrolling of optimization algorithms
SAH Hosseini, B Yaman, S Moeller… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Inverse problems for accelerated MRI typically incorporate domain-specific knowledge
about the forward encoding operator in a regularized reconstruction framework. Recently …
about the forward encoding operator in a regularized reconstruction framework. Recently …
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 …
Deep learning based MRI reconstruction with transformer
Z Wu, W Liao, C Yan, M Zhao, G Liu, N Ma… - Computer Methods and …, 2023 - Elsevier
Magnetic resonance imaging (MRI) has become one of the most powerful imaging
techniques in medical diagnosis, yet the prolonged scanning time becomes a bottleneck for …
techniques in medical diagnosis, yet the prolonged scanning time becomes a bottleneck for …
Recent advances in highly accelerated 3D MRI
Three-dimensional MRI has gained increasing popularity in various clinical applications due
to its improved through-plane spatial resolution, which enhances the detection of subtle …
to its improved through-plane spatial resolution, which enhances the detection of subtle …
Accelerated MRI reconstruction with separable and enhanced low-rank Hankel regularization
Magnetic resonance imaging serves as an essential tool for clinical diagnosis, however,
suffers from a long acquisition time. Sparse sampling effectively saves this time but images …
suffers from a long acquisition time. Sparse sampling effectively saves this time but images …
One-shot generative prior in Hankel-k-space for parallel imaging reconstruction
H Peng, C Jiang, J Cheng, M Zhang… - … on Medical Imaging, 2023 - ieeexplore.ieee.org
Magnetic resonance imaging serves as an essential tool for clinical diagnosis. However, it
suffers from a long acquisition time. The utilization of deep learning, especially the deep …
suffers from a long acquisition time. The utilization of deep learning, especially the deep …
[HTML][HTML] A unified model for reconstruction and R2* map** of accelerated 7T data using the quantitative recurrent inference machine
Quantitative MRI (qMRI) acquired at the ultra-high field of 7 Tesla has been used in
visualizing and analyzing subcortical structures. qMRI relies on the acquisition of multiple …
visualizing and analyzing subcortical structures. qMRI relies on the acquisition of multiple …