Official PyTorch implementation of SAMA-UNet: A novel U-shaped architecture for medical image segmentation that integrates Self-Adaptive Mamba-like Attention and Causal-Resonance Learning.
Abstract: Acquiring high-quality annotated data for medical image segmentation is tedious and costly. Semi-supervised segmentation techniques alleviate this burden by leveraging unlabeled data to ...
Abstract: Medical image segmentation has made significant strides with the development of basic models. Specifically, models that combine CNNs with transformers can successfully extract both local and ...
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