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eess.IV2026
Revisiting Global Token Mixing in Task-Dependent MRI Restoration: Insights from Minimal Gated CNN Baselines
Xiangjian Hou, Chao Qin, Chang Ni +3
Global token mixing, implemented via self-attention or state-space sequence models, has become a popular model design choice for MRI restoration. However, MRI restoration tasks dif…
eess.IV2024
DB-SAM: Delving into High Quality Universal Medical Image Segmentation
Chao Qin, Jiale Cao, Huazhu Fu +2
Recently, the Segment Anything Model (SAM) has demonstrated promising segmentation capabilities in a variety of downstream segmentation tasks. However in the context of universal m…