4 citations · 7 across the 5 of their papers we have counts for
4 papers
Data and Physics Driven Learning Models for Fast MRI -- Fundamentals and Methodologies from CNN, GAN to Attention and Transformers
Jiahao Huang, Yingying Fang, Yang Nan +9
Research studies have shown no qualms about using data driven deep learning models for downstream tasks in medical image analysis, e.g., anatomy segmentation and lesion detection,…
FA-GAN: Fused Attentive Generative Adversarial Networks for MRI Image Super-Resolution
Mingfeng Jiang, Minghao Zhi, Liying Wei +6
High-resolution magnetic resonance images can provide fine-grained anatomical information, but acquiring such data requires a long scanning time. In this paper, a framework called…
Transfer Learning Enhanced Generative Adversarial Networks for Multi-Channel MRI Reconstruction
Jun Lv, Guangyuan Li, Xiangrong Tong +4
Deep learning based generative adversarial networks (GAN) can effectively perform image reconstruction with under-sampled MR data. In general, a large number of training samples ar…
Generative Adversarial Networks (GAN) Powered Fast Magnetic Resonance Imaging -- Mini Review, Comparison and Perspectives
Guang Yang, Jun Lv, Yutong Chen +2
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, superior soft…