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Aeoo/CVC-ClinicDB

CVC-ClinicDB: Colonoscopy Polyp Segmentation Dataset Dataset Description CVC-ClinicDB is a colonoscopy polyp segmentation dataset containing 612 frames extracted from 29 colonoscopy sequences with corresponding ground truth segmentation masks. Task: Binary segmentation (polyp vs. background) Modality: Colonoscopy Format: PNG images (384x288 pixels) with binary masks Splits: Training, Validation, and Test sets Dataset Structure CVC-ClinicDB/ ├──… See the full description on the dataset page: https://huggingface.co/datasets/Aeoo/CVC-ClinicDB.

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Dataset Card

CVC-ClinicDB: Colonoscopy Polyp Segmentation Dataset

Dataset Description

CVC-ClinicDB is a colonoscopy polyp segmentation dataset containing 612 frames extracted from 29 colonoscopy sequences with corresponding ground truth segmentation masks.

—Task: Binary segmentation (polyp vs. background)
—Modality: Colonoscopy
—Format: PNG images (384x288 pixels) with binary masks
—Splits: Training, Validation, and Test sets

Dataset Structure

CVC-ClinicDB/
├── train/
│   ├── images/  # Training images
│   └── masks/   # Training masks
├── validation/
│   ├── images/  # Validation images
│   └── masks/   # Validation masks
└── test/
    ├── images/  # Test images
    └── masks/   # Test masks

Citation

If you use this dataset, please cite:

bibtex

@article{bernal2015wm,
  title={WM-DOVA maps for accurate polyp highlighting in colonoscopy: Validation vs. saliency maps from physicians},
  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},
  journal={Computerized Medical Imaging and Graphics},
  volume={43},
  pages={99--111},
  year={2015},
  publisher={Elsevier}
}

Dataset Split: This train/validation/test split is created by the following study. Please find more details in:

bibtex

@article{chang2024esfpnet,
  title={ESFPNet: Efficient Stage-Wise Feature Pyramid on Mix Transformer for Deep Learning-Based Cancer Analysis in Endoscopic Video},
  author={Chang, Qi and Ahmad, Danish and Toth, Jennifer and Bascom, Rebecca and Higgins, William E},
  journal={Journal of Imaging},
  volume={10},
  number={8},
  pages={191},
  year={2024},
  publisher={MDPI}
}

Usage

python

from datasets import load_dataset

# Load dataset
dataset = load_dataset("Angelou0516/CVC-ClinicDB")

# Access splits
train_data = dataset['train']
val_data = dataset['validation']
test_data = dataset['test']

# Access a sample
sample = train_data[0]
image = sample['file_name']  # Image
mask = sample['mask_file_name']  # Segmentation mask

License