Abstract: Labeling large amounts of medical data is travailing, leading to the blooming of few-shot medical image segmentation, which aims to segment the foreground of a query image given a labeled ...

OpenWorldSAM pushes the boundaries of SAM2 by enabling open-vocabulary segmentation with flexible language prompts. [2026-1-4]: Demo release: we’ve added simple demos to run OpenWorldSAM on images ...

Abstract: Medical image segmentation is an important component of medical image analysis, allowing precise delineation of regions of interest for accurate diagnosis and treatment planning. Deep ...

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.