2 papers
cs.CV2026
Removing Motion Artifact in MRI by Using a Perceptual Loss Driven Deep Learning Framework
Ziheng Guo, Danqun Zheng, Shuai Li +8
Purpose: Deep learning-based MRI artifact correction methods often demonstrate poor generalization to clinical data. This limitation largely stems from the inability of deep learni…
eess.IV2024
HiFi-Syn: Hierarchical Granularity Discrimination for High-Fidelity Synthesis of MR Images with Structure Preservation
Ziqi Yu, Botao Zhao, Shengjie Zhang +4
Synthesizing medical images while preserving their structural information is crucial in medical research. In such scenarios, the preservation of anatomical content becomes especial…