3 citations · 6 across the 3 of their papers we have counts for
3 papers
eess.IV2022★ 3 cited
Transformer-empowered Multi-scale Contextual Matching and Aggregation for Multi-contrast MRI Super-resolution
Guangyuan Li, Jun Lv, Yapeng Tian +4
Magnetic resonance imaging (MRI) can present multi-contrast images of the same anatomical structures, enabling multi-contrast super-resolution (SR) techniques. Compared with SR rec…
eess.IV2021
High-Resolution Pelvic MRI Reconstruction Using a Generative Adversarial Network with Attention and Cyclic Loss
Guangyuan Li, Jun Lv, Xiangrong Tong +2
Magnetic resonance imaging (MRI) is an important medical imaging modality, but its acquisition speed is quite slow due to the physiological limitations. Recently, super-resolution…
eess.IV2021★ 3 cited
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…