Stars
A2FSeg: Adaptive Multi-Modal Fusion Network for Medical Image Segmentation
Language-Driven Semantic Segmentation
[CIBM 2024] Segment Anything Model for Medical Image Segmentation: Open-Source Project Summary
Official implementation of SAM-Med2D
This the repo for the paper tiltled "AgileFormer: Spatially Agile Transformer UNet for Medical Image Segmentation"
[CVPR 2025] Official repository of the paper "Mask-Adapter: The Devil is in the Masks for Open-Vocabulary Segmentation"
Conditional diffusion model with spatial attention and latent embedding for medical image segmentation
SAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation
EasyR1: An Efficient, Scalable, Multi-Modality RL Training Framework based on veRL
nnInteractive is a framework for 3D interactive segmentation, supporting intuitive prompts like points, scribbles, bounding boxes, and lasso. Trained on 120+ diverse 3D datasets, it sets a new stan…
Implementation of the Prithvi WxC Foundation Model and Downstream Tasks
SAM Adaptation for mp-MRI Brain Tumor Segmentation
Segment Anything in Medical Images
This study presents the development and validation of AI models for both nodule detection and cancer classification tasks. This benchmarking across multiple datasets establishes the DLCSD as a reli…
The official repo for "Unified Domain Adaptive Semantic Segmentation" （IEEE TPAMI 2025）
Brain Tumor Segmentation done using U-Net Architecture.
A deep learning based approach for brain tumor MRI segmentation.
Simple PyTorch implementations of U-Net/FullyConvNet (FCN) for image segmentation