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 …
Medical image generation using generative adversarial networks: A review
Generative adversarial networks (GANs) are unsupervised deep learning approach in the
computer vision community which has gained significant attention from the last few years in …
computer vision community which has gained significant attention from the last few years in …
[HTML][HTML] FA-GAN: Fused attentive generative adversarial networks for MRI image super-resolution
High-resolution magnetic resonance images can provide fine-grained anatomical
information, but acquiring such data requires a long scanning time. In this paper, a …
information, but acquiring such data requires a long scanning time. In this paper, a …
Retrospective correction of motion‐affected MR images using deep learning frameworks
Purpose Motion is 1 extrinsic source for imaging artifacts in MRI that can strongly deteriorate
image quality and, thus, impair diagnostic accuracy. In addition to involuntary physiological …
image quality and, thus, impair diagnostic accuracy. In addition to involuntary physiological …
Unsupervised medical image translation using cycle-MedGAN
Image-to-image translation is a new field in computer vision with multiple potential
applications in the medical domain. However, for supervised image translation frameworks …
applications in the medical domain. However, for supervised image translation frameworks …
Motion artifact reduction for magnetic resonance imaging with deep learning and k-space analysis
L Cui, Y Song, Y Wang, R Wang, D Wu, H Xie, J Li… - PloS one, 2023 - journals.plos.org
Motion artifacts deteriorate the quality of magnetic resonance (MR) images. This study
proposes a new method to detect phase-encoding (PE) lines corrupted by motion and …
proposes a new method to detect phase-encoding (PE) lines corrupted by motion and …
Unpaired MR motion artifact deep learning using outlier-rejecting bootstrap aggregation
Recently, deep learning approaches for MR motion artifact correction have been extensively
studied. Although these approaches have shown high performance and lower …
studied. Although these approaches have shown high performance and lower …
Uneven illumination correction of digital images: A survey of the state-of-the-art
N Dey - Optik, 2019 - Elsevier
The common image related artifacts during image acquisition are noise caused due to
external interference and imbalance in illumination. Uneven illumination correction …
external interference and imbalance in illumination. Uneven illumination correction …
Medical image inpainting with edge and structure priors
Image inpainting techniques are widely applied to repair distorted or missing regions in the
image. However, unreasonable results are usually generated due to lack of structural …
image. However, unreasonable results are usually generated due to lack of structural …
A systematic literature review on applications of GAN-synthesized images for brain MRI
With the advances in brain imaging, magnetic resonance imaging (MRI) is evolving as a
popular radiological tool in clinical diagnosis. Deep learning (DL) methods can detect …
popular radiological tool in clinical diagnosis. Deep learning (DL) methods can detect …