This is the code to repoduce the study of Multi-Feature Semi-Supervised Learning for COVID-19 Diagnosis from Chest X-ray Images. Please cite our study if you are using this dataset and referring to our method.
- Test-1
| Method | Labeled Sample (%) | Precision | Recall | F1-Scores | Top-1(%) |
|---|---|---|---|---|---|
| MF-TS | 30 | 0.94 | 0.94 | 0.94 | 93.61 |
- Test-2
| Method | Labeled Sample (%) | Precision | Recall | F1-Scores | Top-1(%) |
|---|---|---|---|---|---|
| MF-TS | 30 | 0.93 | 0.94 | 0.93 | 92.47 |
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Dataset and Trained model weights:
- Download them from Kaggle. CXR folder are all origianl CXR images and Enh folder are all corresponding enhanced images. All weights are in the weight folder
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Preparation:
- Create a folder to save all downloaded files from this repo and files from Kaggle in one folder. Please modify the coloumn of both test_ds.txt and additional_test_ds.txt to the directory where you create the folder
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Test:
- CXR-TS: python Test.py --action=retest --dataset=test_ds/additional_test_ds --per_teacher=0.1/0.2/0.3 (test_ds=Test-1; additiona_test_ds=Test-2; 0.1=10% labeled samples etc.)
- Enh-TS: python Test.py --action=retest --dataset=test_ds/additional_test_ds --type=Enh --per_teacher=0.1/0.2/0.3 (type = image type; default = CXR)
- MF-T: python Test.py --action=retest_based_both --dataset=test_ds/additional_test_ds --per_teacher=0.1/0.2/0.3
- MF-TS: python Test.py --action=latefusion_retest_2models --dataset=test_ds/additional_test_ds --per_teacher=0.1/0.2/0.3