https://github.com/hilab-git/dca-net
https://github.com/hilab-git/dca-net
Last synced: about 1 year ago
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- Host: GitHub
- URL: https://github.com/hilab-git/dca-net
- Owner: HiLab-git
- Created: 2021-07-09T08:42:38.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2024-05-19T12:47:49.000Z (almost 2 years ago)
- Last Synced: 2025-03-20T21:38:54.786Z (about 1 year ago)
- Language: Python
- Size: 56.1 MB
- Stars: 9
- Watchers: 1
- Forks: 1
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation
Pytorch implementation of our 'Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation', which is accepted in MICCAI 2021.
## Usage
### 1. Training StyleGAN
StyleGAN was implemented by following (https://github.com/NVlabs/stylegan2-ada-pytorch), and it was trained for each domain respectively, as `image_gan`.
### 2. Prepare Dataset.
Prepare the following files: `image`, `label`, `image_gan`.
```
├── images
├── label
└── image_gan
```
### 3. Train the model.
1) Modify the configuration settings in settings.ini according to your requirements.
2) Run the training script:
```python
python train_multi_fundus.py
```
### 4. Test the model.
1) Not using TTFA test model.
```python
python test_multi_fundus.py
```
2) Using TTFA test models.
```python
python test_multi_fundus_ttfa.py
```