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Context-Gated Cross-Modal Perception with Visual Mamba for PET-CT Lung Tumor Segmentation
Accurate lung tumor segmentation is vital for improving diagnosis and treatment planning, and effectively combining anatomical and functional information from PET and CT remains a major challenge. In this study, we propose vMambaX, a lightweight multimodal framework integrating PET and CT scan image
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