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20212023
most citedTransfer Learning Enhanced Generative Adversarial Networks for Multi-Channel MRI Reconstruction

3 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2023★ 1 cited

VGOS: Voxel Grid Optimization for View Synthesis from Sparse Inputs

Jiakai Sun, Zhanjie Zhang, Jiafu Chen +5

Neural Radiance Fields (NeRF) has shown great success in novel view synthesis due to its state-of-the-art quality and flexibility. However, NeRF requires dense input views (tens to…

cs.GR2023★ 2 cited

Joint Optimization of Triangle Mesh, Material, and Light from Neural Fields with Neural Radiance Cache

Jiakai Sun, Weijing Zhang, Zhanjie Zhang +4

Traditional inverse rendering techniques are based on textured meshes, which naturally adapts to modern graphics pipelines, but costly differentiable multi-bounce Monte Carlo (MC)…

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…