This MI2RLNet is the hub of pretrained models in the medical domain.

We hope MI2RLNet helps your downstream task.

• Organizing Team : MI2RL, Asan Medical Center(AMC), Seoul, Republic of Korea

• Contributor

  • Commiter : Kyuri Kim, Jiyeon Seo, Jooyoung Park, Mingyu Kim, Kyungjin Cho, Daeun Kim, Yujin Nam.

  • Reviewer : Sungman Cho, Sungchul Kim.

  • Data Maintainer : Miso Jang, Namkug Kim.

    
    

• Docker images

  • Dockerfille : tensorflow > 2.x, Pytorch 1.x

    
    

• The example code below applies to almost all modules. Some modules may require additional parameters.

from medimodule.Abdomen import LiverSegmentation

# Initialize the model.
# If pre-trained weight exists, enter it together when the model is assigned.
model = LiverSegmentation("/path/of/weight")

# Get a result.
# If you want to save the result, enter it with `save_path` kwargs.
image, mask = model.predict("/path/of/image", save_path="/path/for/save")

# Import any module you want to fine-tune.
from medimodule.Abdomen import LiverSegmentation

# Initialize the model with pre-trained weight.
model = LiverSegmentation("/path/of/weight")

# Construct your custom training code.
...
model.train()
...

If you'd like to contribute, or have any suggestions for these guidelines, you can contact us at [email protected] or open an issue on this GitHub repository.

All contributions welcome! All content in this repository is licensed under the Apache 2.0 license.