DOI: 10.5281/zenodo.18106133
title: COBRA data toolkit: A whole-slide image dataset of basal cell carcinoma and diverse skin malignancies for computational dermatopathology

description: COBRA: A whole-slide image dataset of basal cell carcinoma and diverse skin malignancies for computational dermatopathology

Description

We introduce COBRA (Classification Of Basal cell carcinoma, Risky skin tumors and Abnormalities), a comprehensive dermatopathology dataset for computational pathology research. COBRA addresses the need for large-scale, high-quality datasets to train and validate AI models for skin cancer detection, report generation, and out-of-distribution detection.

The dataset contains whole-slide images (WSIs) from Radboud University Medical Center, spanning multiple diagnostic categories including:



Basal Cell Carcinoma

Benign & Pre-malignant lesions

Squamous Cell Carcinoma

Lymphoma

Melanoma

Merkel Cell Carcinoma

Cutaneous Metastases

Rare Adnexal Tumors


All experiment runners include a small subset of the data to verify that everything is working correctly. To access the full dataset, please refer to the documentation at the repository linked below.

Key Features



Multi-level annotations: Slide-level diagnostic labels for all images, pixel-level annotations for resection specimens

Pathology reports: Dutch-language pathology conclusions enabling vision-language model research

Pre-computed embeddings: PRISM foundation model embeddings (slide-level and tile-level) for immediate use

Standardized format: All images bin-packed and resampled to 0.5 µm/pixel in pyramidal TIFF format

Patient metadata: Anonymized demographic information (age, gender)


Repository Structure

cobra/
├── bcc/                    # BCC and benign/pre-malignant biopsies
│   ├── images/             # Whole-slide images (.tif)
│   ├── annotations/        # Slide-level labels
│   ├── metadata/           # Patient metadata
│   ├── reports/            # Pathology conclusions
│   ├── postprocessing/     # PRISM embeddings
│   └── thumbnails/         # Low-resolution previews
├── ood/                    # Out-of-distribution malignancies
│   ├── images/
│   ├── annotations/
│   ├── metadata/
│   ├── postprocessing/
│   └── thumbnails/
└── resections/             # BCC resections with pixel-level annotations
    ├── images/
    ├── annotations/        # GeoJSON polygons and TIFF masks
    │   ├── tumor/
    │   └── epidermis/
    ├── metadata/
    ├── postprocessing/
    └── thumbnails/


Annotation Details

Slide-level Labels

CSV files with columns: filename, label

Pixel-level Annotations (Resections)



GeoJSON polygons: Vector annotations for tumor and epidermis regions

TIFF masks: Single-band masks with class indices (0=background, 1=tissue, 2=tumor, 3=epidermis)


Pathology Reports

CSV files with columns: filename, conclusion (Dutch text)

Technical Specifications




Property
Value




Image format
Pyramidal TIFF (JPEG compression)


Resolution
0.5 µm/pixel


Tile size
256×256 pixels


Color space
RGB, 8-bit per channel




Intended Use

COBRA supports multiple computational pathology tasks:



Binary and multi-class classification of skin lesions

Semantic segmentation of tissue compartments

Out-of-distribution detection for clinical safety

Vision-language model development with pathology reports

Zero-shot classification using foundation model embeddings


License



Dataset: CC BY 4.0

Software: Apache License 2.0


Acknowledgments

The COBRA dataset was made possible through kind donations from:



Mr H.J.M. Roels donation to Oncode Institute

Lionsclub Doetinchem - de Graafschap


Contact



Daan Geijs - Dataset creator

Geert Litjens - Corresponding author (geert.litjens@radboudumc.nl)


Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands

diagnijmegen.nlcomputationalpathologygroup.eu