Semi-Mamba-UNet: A Pixel-Level Contrastive and Cross-Supervised Visual Mamba-based UNet for Semi-Supervised Medical Image Segmentation

This paper introduces the Semi-Mamba-UNet, a novel framework that integrates a purely visual mamba-based U-Shape Encoder-Decoder architecture with a conventional CNN-based UNet into a Semi-Supervised Learning (SSL) framework, leveraging both networks to simultaneously generate pseudo labels and cross supervise each other on the pixel level.