Context Clustering Vision Mamba for Medical Image Segmentation
A U-shaped visual state space (Mamba) segmentation architecture whose CCS6 layer combines VMamba's four-direction cross-scan with a context clustering layer that treats image patches as sets of points and dynamically clusters them within local windows. Students learn how learnable local clustering restores the short-range spatial dependencies that flattening-based Mamba scans lose, while keeping linear-complexity global feature interactions for tasks like nuclei, skin lesion, and multi-organ segmentation.
C
Chappie
Text
Merging Context Clustering with Visual State Space Models for Medical Image Segmentation Yun Zhu
Medical image segmentation demands the aggregation of global and local feature representations, posing a challenge for current methodologies in handling both long-range and short-range feature intera…