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--- |
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license: cc-by-4.0 |
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task_categories: |
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- image-segmentation |
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tags: |
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- medical |
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- polyp-segmentation |
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- colonoscopy |
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- gastrointestinal |
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size_categories: |
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- n<1K |
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pretty_name: CVC-ClinicDB |
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--- |
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# CVC-ClinicDB: Colonoscopy Polyp Segmentation Dataset |
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## Dataset Description |
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CVC-ClinicDB is a colonoscopy polyp segmentation dataset containing 612 frames extracted from 29 colonoscopy sequences with corresponding ground truth segmentation masks. |
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- **Task**: Binary segmentation (polyp vs. background) |
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- **Modality**: Colonoscopy |
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- **Format**: PNG images (384x288 pixels) with binary masks |
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- **Splits**: Training, Validation, and Test sets |
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## Dataset Structure |
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``` |
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CVC-ClinicDB/ |
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├── train/ |
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│ ├── images/ # Training images |
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│ └── masks/ # Training masks |
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├── validation/ |
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│ ├── images/ # Validation images |
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│ └── masks/ # Validation masks |
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└── test/ |
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├── images/ # Test images |
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└── masks/ # Test masks |
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``` |
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## Citation |
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If you use this dataset, please cite: |
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```bibtex |
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@article{bernal2015wm, |
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title={WM-DOVA maps for accurate polyp highlighting in colonoscopy: Validation vs. saliency maps from physicians}, |
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author={Bernal, Jorge and S{'a}nchez, F Javier and Fern{'a}ndez-Esparrach, Gloria and Gil, Debora and Rodr{\'\i}guez, Cristina and Vilari{\~n}o, Fernando}, |
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journal={Computerized Medical Imaging and Graphics}, |
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volume={43}, |
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pages={99--111}, |
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year={2015}, |
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publisher={Elsevier} |
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} |
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``` |
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**Dataset Split**: This train/validation/test split is created by the following study. Please find more details in: |
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```bibtex |
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@article{chang2024esfpnet, |
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title={ESFPNet: Efficient Stage-Wise Feature Pyramid on Mix Transformer for Deep Learning-Based Cancer Analysis in Endoscopic Video}, |
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author={Chang, Qi and Ahmad, Danish and Toth, Jennifer and Bascom, Rebecca and Higgins, William E}, |
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journal={Journal of Imaging}, |
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volume={10}, |
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number={8}, |
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pages={191}, |
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year={2024}, |
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publisher={MDPI} |
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} |
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``` |
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## Usage |
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```python |
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from datasets import load_dataset |
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# Load dataset |
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dataset = load_dataset("Angelou0516/CVC-ClinicDB") |
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# Access splits |
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train_data = dataset['train'] |
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val_data = dataset['validation'] |
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test_data = dataset['test'] |
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# Access a sample |
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sample = train_data[0] |
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image = sample['file_name'] # Image |
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mask = sample['mask_file_name'] # Segmentation mask |
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``` |
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## License |
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Please refer to the original CVC-ClinicDB dataset license and citation requirements. |
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## Links |
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- Original Dataset: https://polyp.grand-challenge.org/CVCClinicDB/ |
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- Paper: https://www.sciencedirect.com/science/article/pii/S0895611115000567 |
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