| --- |
| license: cc-by-nc-sa-4.0 |
| task_categories: |
| - image-segmentation |
| tags: |
| - medical |
| - histopathology |
| - h-and-e |
| - nuclei |
| - instance-segmentation |
| - pan-cancer |
| - tcga |
| - gtex |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # PanNuke |
|
|
| Pan-Cancer H&E Nuclei Instance Segmentation and Classification dataset |
| (Gamper et al., ECDP 2019; arXiv:2003.10778). Mirrored from the |
| [Warwick TIA Centre release](https://warwick.ac.uk/fac/cross_fac/tia/data/pannuke). |
|
|
| ## Composition |
|
|
| - **7,901** RGB patches of 256x256 at 40x magnification (~0.25 um/pixel) |
| - **19** tissue types pooled from TCGA / GTEx (Breast, Colon, Lung, Kidney, |
| Prostate, Stomach, Ovarian, Bladder, Esophagus, Pancreatic, Thyroid, Skin, |
| Cervix, Adrenal_gland, Bile-duct, Liver, HeadNeck, Testis, Uterus) |
| - **~189,744** annotated nuclei, multi-pathologist QC |
| - **3 folds** (PanNuke is designed for 3-fold cross-validation): |
| - `fold1`: 2,656 patches |
| - `fold2`: 2,523 patches |
| - `fold3`: 2,722 patches |
| |
| ## Schema |
| |
| | Field | Type | Description | |
| |---------------|-------------------------------|-------------------------------------------------------| |
| | `image` | PIL RGB 256x256 | H&E patch, uint8 | |
| | `inst_map` | PIL grayscale uint16 256x256 | Global per-pixel instance ID (0 = background) | |
| | `type_map` | PIL grayscale uint8 256x256 | Semantic class per pixel (see table below) | |
| | `tissue` | int | Tissue ID 0-18 (alphabetical) | |
| | `tissue_name` | str | Tissue type name | |
| | `fold` | int | Source fold (1, 2, or 3) | |
| | `sample_id` | str | Unique ID, `foldN_NNNN` | |
|
|
| ### Semantic class encoding (`type_map`) |
| |
| | Value | Class | |
| |-------|--------------------------| |
| | 0 | Background | |
| | 1 | Neoplastic | |
| | 2 | Inflammatory | |
| | 3 | Connective / Soft tissue | |
| | 4 | Dead | |
| | 5 | Epithelial | |
| |
| ### Instance map (`inst_map`) |
|
|
| Each connected nucleus is assigned a unique 16-bit integer ID per patch |
| (starting from 1). IDs are derived from the original 6-channel mask |
| arrays released by Warwick: for each foreground class channel, instance |
| IDs are offset by the running count of nuclei in previous channels so |
| the result is globally unique within the patch. |
|
|
| ## License |
|
|
| CC BY-NC-SA 4.0 (research / non-commercial use). Same license as the |
| original Warwick release. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{gamper2020pannuke, |
| title={PanNuke Dataset Extension, Insights and Baselines}, |
| author={Gamper, Jevgenij and Koohbanani, Navid Alemi and Graham, Simon and Jahanifar, Mostafa and Benet, Ksenija and Khurram, Syed Ali and Azam, Ayesha and Hewitt, Katherine and Rajpoot, Nasir}, |
| journal={arXiv preprint arXiv:2003.10778}, |
| year={2020} |
| } |
| |
| @inproceedings{gamper2019pannuke, |
| title={Pannuke: An open pan-cancer histology dataset for nuclei instance segmentation and classification}, |
| author={Gamper, Jevgenij and Koohbanani, Navid Alemi and Benet, Ksenija and Khuram, Ali and Rajpoot, Nasir}, |
| booktitle={European Congress on Digital Pathology}, |
| pages={11--19}, |
| year={2019}, |
| organization={Springer} |
| } |
| ``` |
|
|
