GraphCovidNet

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COVID-19 scan image detection using GraphCovidNet (GIN model)

GraphCovidNet 최신버젼 다운로드

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# GraphCovidNet
COVID-19 CT-scan and CXR image detection using GraphCovidNet, a GIN based architecture. The code has been performed on 2-class,3-class and 4-class datasets.

# Dataset link
```
1. SARS-COV-2 Ct-Scan Dataset, CT-scan, 2-class: https://www.kaggle.com/plameneduardo/sarscov2-ctscan-dataset
2. COVID-CT Dataset, CT-scan, 2-class: https://github.com/UCSD-AI4H/COVID-CT
3. covid-chest-xray dataset: https://github.com/ieee8023/covid-chestxray-dataset + Chest X-Ray Images (Pneumonia): https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia , CXR, 3-class
4. CMSC-678-ML-Project, CXR, 3/4-class: https://github.com/vj2050/Transfer-Learning-COVID-19
```
# File Structure and Working procedure
```
1. First apply edge detection accroding to the class-number: Edge detection/edge_detection_<class-number>class.py
2. Then prepare graph-datasets using edge-preparation: Edge preparation/edge_preparation_<class-number>class.py
3. Finally edge preperation produces five kinds of dataset for graph classification:
  path name: .../GraphTrain/dataset/<dataset_name>/raw/<dataset_name>_<data_file>.txt. 
  <data_file> can be:
    
    1. A--> adjancency matrix 
    2. graph_indicator--> graph-ids of all node 
    3. graph_labels--> labels for all graph 
    4. node_attributes--> attribute(s) for all node 
    5. node_labels--> labels for all node
4. After all the graph datasets are created properly, run main.py. The graph datasets are loaded through dataloader.py and the model is called through model.py
```

# Citation
We have published our work entitled as "GraphCovidNet: a graph neural network based model for detecting COVID‑19 from CT scans and X‑rays of chest" under the "scientific reports" issue of "nature" journal. If this repository helps you in your research in any way, please cite our paper:
```
@article{saha2021GraphCovidNet,
  title={GraphCovidNet: a graph neural network based model for detecting COVID‑19 from CT scans and X‑rays of chest}
  author={Saha, Pritam and Mukherjee,  Debadyuti and Singh,Pawan and Ahmadian, ALi and Ferrara, Massimiliano and  Sarkar, Ram}
}
```

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