This repository is an official PyTorch implementation of the paper "UN-SAM: Universal Prompt-Free Segmentation for Generalized Nucleus Images" [paper] submitted to IEEE Transactions on Medical Imaging.
- Python 3.10
- PyTorch >= 1.10.0
- albumentations 1.5.2
- monai 1.3.0
- pytorch_lightning 1.1.0
Clone this repository into any place you want.
git clone https://github.com/CUHK-AIM-Group/UNSAM.git
cd UNSAM
mkdir data; mkdir pretrain;
- Train the UN-SAM with the default settings:
python train.py --dataset data/$YOUR DATASET NAME$ --sam_pretrain pretrain/$SAM CHECKPOINT$
If you find our work useful in your research or publication, please cite our work:
@article{chen2024sam,
title={UN-SAM: Universal Prompt-Free Segmentation for Generalized Nuclei Images},
author={Chen, Zhen and Xu, Qing and Liu, Xinyu and Yuan, Yixuan},
journal={arXiv preprint arXiv:2402.16663},
year={2024}
}