AI RESEARCH
MD-RWKV-UNet: Scale-Aware Anatomical Encoding with Cross-Stage Fusion for Multi-Organ Segmentation
arXiv CS.CV
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ArXi:2603.27261v1 Announce Type: new Multi-organ segmentation in medical imaging remains challenging due to large anatomical variability, complex inter-organ dependencies, and diverse organ scales and shapes. Conventional encoder-decoder architectures often struggle to capture both fine-grained local details and long-range context, which are crucial for accurate delineation - especially for small or deformable organs. To address these limitations, we propose MD-RWKV-UNet, a dynamic encoder network that enables scale-aware representation and spatially adaptive context modeling.