Skip to content
/ SIFA Public
forked from cchen-cc/SIFA

[AAAI'19] Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation

Notifications You must be signed in to change notification settings

carrenD/SIFA

 
 

Repository files navigation

SIFA

Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation

Installation

  • Install TensorFlow 1.4 and CUDA 8.0
  • Clone this repo
git clone https://github.com/cchen-cc/SIFA
cd SIFA

Data Preparation

  • Raw data needs to be written into tfrecord format to be decoded by ./data_loader.py.
  • Put tfrecord data of two domains into corresponding folders under ./data accordingly.
  • Run ./create_datalist.py to generate the datalists containing the path of each data.

Train

  • Modify paramter values in ./config_param.json
  • Run ./main.py to start the training process


If you make use of the code, please cite the paper in resulting publications.

@article{chen2019synergistic,
  title={Synergistic image and feature adaptation: Towards cross-modality domain adaptation for medical image segmentation},
  author={Chen, Cheng and Dou, Qi and Chen, Hao and Qin, Jing and Heng, Pheng-Ann},
  journal={AAAI},
  year={2019}
}

About

[AAAI'19] Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%