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Jul 14, 2020
Jul 14, 2020
Sep 8, 2020

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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