[HTML][HTML] Super-resolution of cardiac MR cine imaging using conditional GANs and unsupervised transfer learning
Y Xia, N Ravikumar, JP Greenwood, S Neubauer… - Medical Image …, 2021 - Elsevier
Abstract High-resolution (HR), isotropic cardiac Magnetic Resonance (MR) cine imaging is
challenging since it requires long acquisition and patient breath-hold times. Instead, 2D …
challenging since it requires long acquisition and patient breath-hold times. Instead, 2D …
Anisotropic super resolution in prostate MRI using super resolution generative adversarial networks
Acquiring High Resolution (HR) Magnetic Resonance (MR) images requires the patient to
remain still for long periods of time, which causes patient discomfort and increases the …
remain still for long periods of time, which causes patient discomfort and increases the …
A generative adversarial network technique for high-quality super-resolution reconstruction of cardiac magnetic resonance images
M Zhao, Y Wei, KKL Wong - Magnetic Resonance Imaging, 2022 - Elsevier
Purpose In this paper, we proposed a Denoising Super-resolution Generative Adversarial
Network (DnSRGAN) method for high-quality super-resolution reconstruction of noisy …
Network (DnSRGAN) method for high-quality super-resolution reconstruction of noisy …
Deep learning single-frame and multiframe super-resolution for cardiac MRI
Background Cardiac MRI is limited by long acquisition times, yet faster acquisition of smaller-
matrix images reduces spatial detail. Deep learning (DL) might enable both faster …
matrix images reduces spatial detail. Deep learning (DL) might enable both faster …
Multi-input cardiac image super-resolution using convolutional neural networks
Abstract 3D cardiac MR imaging enables accurate analysis of cardiac morphology and
physiology. However, due to the requirements for long acquisition and breath-hold, the …
physiology. However, due to the requirements for long acquisition and breath-hold, the …
Super resolution of cardiac cine MRI sequences using deep learning
Cardiac cine MRI facilitates structural and functional analysis of the heart through the
dynamic aspect of the sequences. Clinical acquisitions consist of sparse 2D images instead …
dynamic aspect of the sequences. Clinical acquisitions consist of sparse 2D images instead …
Super-resolution of cardiac magnetic resonance images using Laplacian Pyramid based on Generative Adversarial Networks
M Zhao, X Liu, H Liu, KKL Wong - Computerized Medical Imaging and …, 2020 - Elsevier
Background and objective Cardiac magnetic resonance imaging (MRI) can assist in both
functional and structural analysis of the heart, but due to hardware and physical limitations …
functional and structural analysis of the heart, but due to hardware and physical limitations …
[HTML][HTML] SOUP-GAN: Super-resolution MRI using generative adversarial networks
There is a growing demand for high-resolution (HR) medical images for both clinical and
research applications. Image quality is inevitably traded off with acquisition time, which in …
research applications. Image quality is inevitably traded off with acquisition time, which in …
Scan-specific generative neural network for MRI super-resolution reconstruction
The interpretation and analysis of Magnetic resonance imaging (MRI) benefit from high
spatial resolution. Unfortunately, direct acquisition of high spatial resolution MRI is time …
spatial resolution. Unfortunately, direct acquisition of high spatial resolution MRI is time …
Super-resolution of magnetic resonance images using Generative Adversarial Networks
Abstract Magnetic Resonance Imaging (MRI) typically comes at the cost of small spatial
coverage, high expenses and long scan times. Accelerating MRI acquisition by taking less …
coverage, high expenses and long scan times. Accelerating MRI acquisition by taking less …