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LambdaUNet

Pytorch Implementation for our MICCAI 2021 paper: LambdaUNet: 2.5D Stroke Lesion Segmentation of Diffusion-weighted MR Images.

Overview

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Installation

Environment

  • Tested OS: Linux
  • Python >= 3.6

Dependencies:

  1. Install PyTorch 1.4.0 with the correct CUDA version.
  2. Install the dependencies:
    pip install -r requirements.txt
    
    

Datasets

We will release the dataset soon.

Training

You can train your own models with your customized configs and dataset. For example:

python lit_train.py --c samlpe -f 0

Acknowledgment

This repo borrows code from

Citation

If you find our work useful in your research, please cite our paper:

@article{ou2021lambdaunet,
  title={LambdaUNet: 2.5 D Stroke Lesion Segmentation of Diffusion-weighted MR Images},
  author={Ou, Yanglan and Yuan, Ye and Huang, Xiaolei and Wong, Kelvin and Volpi, John and Wang, James Z and Wong, Stephen TC},
  journal={arXiv preprint arXiv:2104.13917},
  year={2021}
}

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