13 citations · 14 across the 7 of their papers we have counts for
4 papers · 1 filter
From Coarse to Continuous: Progressive Refinement Implicit Neural Representation for Motion-Robust Anisotropic MRI Reconstruction
Zhenxuan Zhang, Lipei Zhang, Yanqi Cheng +10
In motion-robust magnetic resonance imaging (MRI), slice-to-volume reconstruction is critical for recovering anatomically consistent 3D brain volumes from 2D slices, especially und…
RSFR: A Coarse-to-Fine Reconstruction Framework for Diffusion Tensor Cardiac MRI with Semantic-Aware Refinement
Jiahao Huang, Fanwen Wang, Pedro F. Ferreira +14
Cardiac diffusion tensor imaging (DTI) offers unique insights into cardiomyocyte arrangements, bridging the gap between microscopic and macroscopic cardiac function. However, its c…
Task-oriented Uncertainty Collaborative Learning for Label-Efficient Brain Tumor Segmentation
Zhenxuan Zhang, Hongjie Wu, Jiahao Huang +5
Multi-contrast magnetic resonance imaging (MRI) plays a vital role in brain tumor segmentation and diagnosis by leveraging complementary information from different contrasts. Each…
Pretext Task Adversarial Learning for Unpaired Low-field to Ultra High-field MRI Synthesis
Zhenxuan Zhang, Peiyuan Jing, Coraline Beitone +4
Given the scarcity and cost of high-field MRI, the synthesis of high-field MRI from low-field MRI holds significant potential when there is limited data for training downstream tas…