Semi-Supervised Biomedical Image Segmentation via Diffusion Models and Teacher-Student Co-Training

Supervised deep learning achieves strong performance in biomedical image segmentation but relies on costly pixel-wise annotations, motivating semi-supervised approaches that exploit unlabeled data. We introduce a diffusion-based teacher--student framework in which segmentation predictions are used t