activity
20242026
most citedSMAFormer: Synergistic Multi-Attention Transformer for Medical Image Segmentation

2 citations · 2 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2026

ScribbleDose: Scribble-Guided Dose Prediction in Radiotherapy

Zhenxi Zhang, Yitao Zhuang, Yao Pu +7

Anatomical structure masks are widely adopted in radiotherapy dose prediction, as they provide explicit geometric constraints that facilitate structure-dose coupling. However, conv…

cs.CV2026

TopoMamba: Topology-Aware Scanning and Fusion for Segmenting Heterogeneous Medical Visual Media

Fuchen Zheng, Chengpei Xu, Long Ma +10

Visual state-space models (SSMs) have shown strong potential for medical image segmentation, yet their effectiveness is often limited by two practical issues: axis-biased scan orde…

cs.CV2025

HBFormer: A Hybrid-Bridge Transformer for Microtumor and Miniature Organ Segmentation

Fuchen Zheng, Xinyi Chen, Weixuan Li +6

Medical image segmentation is a cornerstone of modern clinical diagnostics. While Vision Transformers that leverage shifted window-based self-attention have established new benchma…

cs.CV2025

Adaptive Morph-Patch Transformer for Aortic Vessel Segmentation

Zhenxi Zhang, Fuchen Zheng, Adnan Iltaf +6

Accurate segmentation of aortic vascular structures is critical for diagnosing and treating cardiovascular diseases.Traditional Transformer-based models have shown promise in this…

cs.CV2024

Underwater Image Restoration via Polymorphic Large Kernel CNNs

Xiaojiao Guo, Yihang Dong, Xuhang Chen +4

Underwater Image Restoration (UIR) remains a challenging task in computer vision due to the complex degradation of images in underwater environments. While recent approaches have l…

cs.CV2024

Lagrange Duality and Compound Multi-Attention Transformer for Semi-Supervised Medical Image Segmentation

Fuchen Zheng, Quanjun Li, Weixuan Li +5

Medical image segmentation, a critical application of semantic segmentation in healthcare, has seen significant advancements through specialized computer vision techniques. While d…