| --- |
| license: cc-by-4.0 |
| language: |
| - en |
| pretty_name: PolypGen2021 Processed Binary Segmentation |
| task_categories: |
| - image-to-image |
| tags: |
| - medical |
| - colonoscopy |
| - polyp-segmentation |
| - binary-segmentation |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # PolypGen2021 Processed Binary Segmentation |
|
|
| Processed PolypGen2021 colonoscopy dataset for prompt-guided binary polyp segmentation. |
|
|
| ## Download and extract |
|
|
| Download `PolypGen2021.tar`, then extract it: |
|
|
| ```bash |
| tar -xf PolypGen2021.tar |
| ``` |
|
|
| The extracted layout is: |
|
|
| ```text |
| PolypGen2021/ |
| └── PolypGen2021_binary/ |
| ├── train/ |
| │ ├── references/ |
| │ └── targets/ |
| └── validation/ |
| ├── references/ |
| ├── targets/ |
| └── specs/ |
| ``` |
|
|
| ## Processing summary |
|
|
| - 8,037 total samples. |
| - Train: 6,429 samples. |
| - Validation: 1,608 samples. |
| - All 4,275 source negative samples are retained. |
| - No test split and no overlay images. |
| - Reference images are PNG files. |
| - Binary targets use `[0, 255, 0]` for polyp tissue and `[0, 0, 0]` for background. |
| - A target is entirely black when no polyp is present. |
| - Six prompt templates are assigned deterministically with seed 42. |
| - Validation includes one JSON evaluation spec per sample. |
|
|
| Archive SHA-256: |
|
|
| ```text |
| 411f4e3853862b6760f28b694be0bbf9c63149f382519a48962188fb78c9faf2 |
| ``` |
|
|
| ## Source and license |
|
|
| This is a processed derivative of the PolypGen dataset: |
|
|
| - Official project: https://github.com/DebeshJha/PolypGen |
| - Dataset paper: https://doi.org/10.1038/s41597-023-01981-y |
| - Source mirror used for this processing run: https://www.kaggle.com/datasets/kokoroou/polypgen2021 |
|
|
| The official PolypGen release is published under the Creative Commons Attribution 4.0 International license (CC BY 4.0). Users should cite the original paper and comply with the original dataset terms. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{ali2023multi, |
| title={A multi-centre polyp detection and segmentation dataset for generalisability assessment}, |
| author={Ali, Sharib and Jha, Debesh and Ghatwary, Noha and Realdon, Stefano and Cannizzaro, Renato and Salem, Osama E and Lamarque, Dominique and Daul, Christian and Riegler, Michael A and Anonsen, Kim V and others}, |
| journal={Scientific Data}, |
| volume={10}, |
| number={1}, |
| pages={75}, |
| year={2023} |
| } |
| ``` |
|
|
