Abstract: This paper presents a novel methodology for generating synthetic images that adhere accurately to provided semantic segmentation maps using the Stable Diffusion model with the ControlNet ...
Abstract: Weakly-supervised learning methods have become increasingly attractive for medical image segmentation, but suffered from a high dependence on quantifying the pixel-wise affinities of ...
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.