Generative adversarial network in medical imaging: A review
Generative adversarial networks have gained a lot of attention in the computer vision
community due to their capability of data generation without explicitly modelling the …
community due to their capability of data generation without explicitly modelling the …
GANs for medical image analysis
Generative adversarial networks (GANs) and their extensions have carved open many
exciting ways to tackle well known and challenging medical image analysis problems such …
exciting ways to tackle well known and challenging medical image analysis problems such …
DAGAN: deep de-aliasing generative adversarial networks for fast compressed sensing MRI reconstruction
Compressed sensing magnetic resonance imaging (CS-MRI) enables fast acquisition, which
is highly desirable for numerous clinical applications. This can not only reduce the scanning …
is highly desirable for numerous clinical applications. This can not only reduce the scanning …
Low-dose CT image denoising using a generative adversarial network with Wasserstein distance and perceptual loss
The continuous development and extensive use of computed tomography (CT) in medical
practice has raised a public concern over the associated radiation dose to the patient …
practice has raised a public concern over the associated radiation dose to the patient …
Compressed sensing MRI reconstruction using a generative adversarial network with a cyclic loss
TM Quan, T Nguyen-Duc… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Compressed sensing magnetic resonance imaging (CS-MRI) has provided theoretical
foundations upon which the time-consuming MRI acquisition process can be accelerated …
foundations upon which the time-consuming MRI acquisition process can be accelerated …
How generative adversarial networks promote the development of intelligent transportation systems: A survey
In current years, the improvement of deep learning has brought about tremendous changes:
As a type of unsupervised deep learning algorithm, generative adversarial networks (GANs) …
As a type of unsupervised deep learning algorithm, generative adversarial networks (GANs) …
Real‐time cardiovascular MR with spatio‐temporal artifact suppression using deep learning–proof of concept in congenital heart disease
Purpose Real‐time assessment of ventricular volumes requires high acceleration factors.
Residual convolutional neural networks (CNN) have shown potential for removing artifacts …
Residual convolutional neural networks (CNN) have shown potential for removing artifacts …
Quantitative susceptibility mapping using deep neural network: QSMnet
Deep neural networks have demonstrated promising potential for the field of medical image
reconstruction, successfully generating high quality images for CT, PET and MRI. In this …
reconstruction, successfully generating high quality images for CT, PET and MRI. In this …
A transfer‐learning approach for accelerated MRI using deep neural networks
Purpose Neural networks have received recent interest for reconstruction of undersampled
MR acquisitions. Ideally, network performance should be optimized by drawing the training …
MR acquisitions. Ideally, network performance should be optimized by drawing the training …
Unpaired deep learning for accelerated MRI using optimal transport driven CycleGAN
Recently, deep learning approaches for accelerated MRI have been extensively studied
thanks to their high performance reconstruction in spite of significantly reduced run-time …
thanks to their high performance reconstruction in spite of significantly reduced run-time …