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Learning Directional Feature Maps for Cardiac MRI Segmentation (MICCAI2020)

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DirectionalFeature

This repository contains the code of the following paper "Learning Directional Feature Maps for Cardiac MRI Segmentation (published in MICCAI2020)", https://arxiv.org/abs/2007.11349

Citation

Please cite the related works in your publications if it helps your research:

@inproceedings{cheng2020learning,
  title={Learning directional feature maps for cardiac mri segmentation},
  author={Cheng, Feng and Chen, Cheng and Wang, Yukang and Shi, Heshui and Cao, Yukun and Tu, Dandan and Zhang, Changzheng and Xu, Yongchao},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={108--117},
  year={2020},
  organization={Springer}
}

Usage

ACDC Data Preparation

  1. Register and download ACDC-2017 dataset from https://www.creatis.insa-lyon.fr/Challenge/acdc/index.html
  2. Create a folder outside the project with name ACDC_DataSet and copy the dataset.
  3. From the project folder open file acdc_data_preparation.py.
  4. In the file, set the path to ACDC training dataset is pointed as: complete_data_path = '../../ACDC_DataSet/training' .
  5. Run the script acdc_data_preparation.py.
  6. The processed data for training is generated outside the project folder named processed_acdc_dataset.
  7. Run the ./libs/datastes/gen_acdcjson.py to generate the data list for ACDC training and validation.

Training

cd ./tools
python -m torch.distributed.launch --nproc_per_node 4 --master_port $RANDOM train.py --batch_size 12 --mgpus 0,1,2,3 --output_dir logs/... --train_with_eval

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Learning Directional Feature Maps for Cardiac MRI Segmentation (MICCAI2020)

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