The role of generative adversarial networks in brain MRI: a scoping review
The performance of artificial intelligence (AI) for brain MRI can improve if enough data are
made available. Generative adversarial networks (GANs) showed a lot of potential to …
made available. Generative adversarial networks (GANs) showed a lot of potential to …
[HTML][HTML] Swin transformer for fast MRI
Magnetic resonance imaging (MRI) is an important non-invasive clinical tool that can
produce high-resolution and reproducible images. However, a long scanning time is …
produce high-resolution and reproducible images. However, a long scanning time is …
Regularising inverse problems with generative machine learning models
Deep neural network approaches to inverse imaging problems have produced impressive
results in the last few years. In this survey paper, we consider the use of generative models …
results in the last few years. In this survey paper, we consider the use of generative models …
GAN-based approaches for generating structured data in the medical domain
Modern machine and deep learning methods require large datasets to achieve reliable and
robust results. This requirement is often difficult to meet in the medical field, due to data …
robust results. This requirement is often difficult to meet in the medical field, due to data …
The state-of-the-art in cardiac mri reconstruction: Results of the cmrxrecon challenge in miccai 2023
Cardiac MRI, crucial for evaluating heart structure and function, faces limitations like slow
imaging and motion artifacts. Undersampling reconstruction, especially data-driven …
imaging and motion artifacts. Undersampling reconstruction, especially data-driven …
Deep learning for accelerated and robust MRI reconstruction
Deep learning (DL) has recently emerged as a pivotal technology for enhancing magnetic
resonance imaging (MRI), a critical tool in diagnostic radiology. This review paper provides …
resonance imaging (MRI), a critical tool in diagnostic radiology. This review paper provides …
Edge-enhanced dual discriminator generative adversarial network for fast MRI with parallel imaging using multi-view information
In clinical medicine, magnetic resonance imaging (MRI) is one of the most important tools for
diagnosis, triage, prognosis, and treatment planning. However, MRI suffers from an inherent …
diagnosis, triage, prognosis, and treatment planning. However, MRI suffers from an inherent …
High-Resolution 3D MRI With Deep Generative Networks via Novel Slice-Profile Transformation Super-Resolution
High-resolution magnetic resonance imaging (MRI) sequences, such as 3D turbo or fast
spin-echo (TSE/FSE) imaging, are clinically desirable but suffer from long scanning time …
spin-echo (TSE/FSE) imaging, are clinically desirable but suffer from long scanning time …
Semi-supervised CycleGAN for domain transformation of chest CT images and its application to opacity classification of diffuse lung diseases
S Mabu, M Miyake, T Kuremoto, S Kido - International Journal of Computer …, 2021 - Springer
Purpose The performance of deep learning may fluctuate depending on the imaging devices
and settings. Although domain transformation such as CycleGAN for normalizing images is …
and settings. Although domain transformation such as CycleGAN for normalizing images is …
Generative Adversarial Networks (GAN) Powered Fast Magnetic Resonance Imaging--Mini Review, Comparison and Perspectives
Magnetic Resonance Imaging (MRI) is a vital component of medical imaging. When
compared to other image modalities, it has advantages such as the absence of radiation …
compared to other image modalities, it has advantages such as the absence of radiation …