# DirectionalFeature

**Repository Path**: a243269910/DirectionalFeature

## Basic Information

- **Project Name**: DirectionalFeature
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2022-01-24
- **Last Updated**: 2022-01-24

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 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

![](./pipeline.png)
## 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
```