MGDUN: An interpretable network for multi-contrast MRI image super-resolution reconstruction
Magnetic resonance imaging (MRI) Super-Resolution (SR) aims to obtain high resolution
(HR) images with more detailed information for precise diagnosis and quantitative image …
(HR) images with more detailed information for precise diagnosis and quantitative image …
Hfgn: High-frequency residual feature guided network for fast mri reconstruction
Abstract Magnetic Resonance Imaging (MRI) is a valuable medical imaging technology,
while it suffers from a long acquisition time. Various methods have been proposed to …
while it suffers from a long acquisition time. Various methods have been proposed to …
Deep unfolding network with spatial alignment for multi-modal mri reconstruction
Abstract Multi-modal Magnetic Resonance Imaging (MRI) offers complementary diagnostic
information, but some modalities are limited by the long scanning time. To accelerate the …
information, but some modalities are limited by the long scanning time. To accelerate the …
Joint Under-Sampling Pattern and Dual-Domain Reconstruction for Accelerating Multi-Contrast MRI
Multi-Contrast Magnetic Resonance Imaging (MCMRI) utilizes the short-time reference
image to facilitate the reconstruction of the long-time target one, providing a new solution for …
image to facilitate the reconstruction of the long-time target one, providing a new solution for …
Deep learning-based magnetic resonance image super-resolution: a survey
Z Ji, B Zou, X Kui, J Liu, W Zhao, C Zhu, P Dai… - Neural Computing and …, 2024 - Springer
Magnetic resonance imaging (MRI) is a medical imaging technique used to show
anatomical structures and physiological processes of the human body. Due to limitations like …
anatomical structures and physiological processes of the human body. Due to limitations like …
Brain MRI Image Super-Resolution Reconstruction: A Systematic Review
Magnetic Resonance Imaging (MRI) is pivotal in clinical diagnostics and neurological
research, providing high-contrast, non-invasive imaging. However, the acquisition of high …
research, providing high-contrast, non-invasive imaging. However, the acquisition of high …
Misalignment-Resistant Deep Unfolding Network for multi-modal MRI super-resolution and reconstruction
Abstract Multi-modal Magnetic Resonance Imaging (MRI) super-resolution (SR) and
reconstruction aims to obtain a high-quality target image from corresponding sparsely …
reconstruction aims to obtain a high-quality target image from corresponding sparsely …
A Trust-Guided Approach to MR Image Reconstruction with Side Information
Reducing MRI scan times can improve patient care and lower healthcare costs. Many
acceleration methods are designed to reconstruct diagnostic-quality images from limited …
acceleration methods are designed to reconstruct diagnostic-quality images from limited …
Re-Visible Dual-Domain Self-Supervised Deep Unfolding Network for MRI Reconstruction
Magnetic Resonance Imaging (MRI) is widely used in clinical practice, but suffered from
prolonged acquisition time. Although deep learning methods have been proposed to …
prolonged acquisition time. Although deep learning methods have been proposed to …
Spatial and Modal Optimal Transport for Fast Cross-Modal MRI Reconstruction
Multi-modal magnetic resonance imaging (MRI) plays a crucial role in comprehensive
disease diagnosis in clinical medicine. However, acquiring certain modalities, such as T2 …
disease diagnosis in clinical medicine. However, acquiring certain modalities, such as T2 …