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CereTS: [Unsupervised Domain Adaptation for Cross-Modality Cerebrovascular Segmentation]

This repository provides a PyTorch implementation of our work submitted to TMI. The paper is currently under review.

Overview

  • Model: A novel unsupervised domain adaptation (UDA) framework with image-level, patch-level and feature-level alignments
  • Task: Cross-Modality Cerebrovascular Segmentation
  • Data: TOF-MRA and CTA

Updates

  • 2023.08: Code released.
  • 2024.02.06: Repo improved.
  • The complete code and tutorial will be released soon.

1. Data preparation

  • To be released.

2. Environment

  • Please prepare an environment with python=3.8, and then use the command "pip install -r requirements.txt" for more dependencies.

3. Train

If you have already arranged your data, you can start training your model.

cd "/home/...  .../CereTS/"
python train.py -name <your path to save>

4. Test

After finishing training, you can start testing your model.

python test.py -ckpt_path <your checkpoint path> -save_path <your save path> -target_npy_dirpath <your input path>

Citation

  • To be released.

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