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--- |
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license: cc-by-4.0 |
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task_categories: |
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- image-classification |
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tags: |
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- pathology |
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- histopathology |
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- prostate-cancer |
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- gleason-grading |
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- foundation-models |
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- benchmark |
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size_categories: |
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- 1K<n<10K |
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dataset_info: |
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features: |
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- name: image |
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dtype: image |
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- name: label |
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dtype: int64 |
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- name: slide_id |
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dtype: string |
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splits: |
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- name: baseline |
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|
num_bytes: 298170963 |
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num_examples: 3872 |
|
|
- name: color_jitter |
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|
num_bytes: 287314003 |
|
|
num_examples: 3872 |
|
|
- name: grayscale |
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|
num_bytes: 167680581 |
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|
num_examples: 3872 |
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|
- name: gaussian_noise |
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num_bytes: 458559156 |
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num_examples: 3872 |
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|
- name: heavy_geometric |
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|
num_bytes: 294975593 |
|
|
num_examples: 3872 |
|
|
- name: combined_aggressive |
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|
num_bytes: 449136407 |
|
|
num_examples: 3872 |
|
|
- name: macenko_normalization |
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|
num_bytes: 303746938 |
|
|
num_examples: 3872 |
|
|
- name: hed_stain_augmentation |
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|
num_bytes: 296645574 |
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num_examples: 3872 |
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download_size: 2556068549 |
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dataset_size: 2556229215 |
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configs: |
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- config_name: default |
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data_files: |
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- split: baseline |
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path: data/baseline-* |
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- split: color_jitter |
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path: data/color_jitter-* |
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- split: grayscale |
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path: data/grayscale-* |
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- split: gaussian_noise |
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path: data/gaussian_noise-* |
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|
- split: heavy_geometric |
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path: data/heavy_geometric-* |
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- split: combined_aggressive |
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path: data/combined_aggressive-* |
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- split: macenko_normalization |
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path: data/macenko_normalization-* |
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- split: hed_stain_augmentation |
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path: data/hed_stain_augmentation-* |
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--- |
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# PANDA-PLUS-Bench |
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A benchmark dataset for evaluating WSI-specific feature collapse in pathology foundation models. |
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## Dataset Description |
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PANDA-PLUS-Bench contains expert-annotated prostate biopsy patches from 9 whole slide images (9 unique patients) with pixel-level Gleason pattern annotations. |
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### Dataset Summary |
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- **Patches**: ~2,770 per augmentation condition |
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- **Resolution**: 224×224 pixels at 20× magnification |
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- **Classes**: Benign (0), GP3 (1), GP4 (2), GP5 (3) |
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- **Slides**: 9 (one per patient) |
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- **Augmentations**: 8 conditions |
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### Augmentation Conditions |
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| Split | Description | |
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|-------|-------------| |
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| baseline | ImageNet normalization only | |
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| color_jitter | Brightness, contrast, saturation, hue | |
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| grayscale | Complete color removal | |
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| gaussian_noise | Additive noise (σ=0.05) | |
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| heavy_geometric | Rotation ±180°, flips | |
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| combined_aggressive | All augmentations combined | |
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| macenko_normalization | Stain normalization | |
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| hed_stain_augmentation | H/E channel perturbation | |
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## Usage |
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```python |
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from datasets import load_dataset |
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# Load baseline patches |
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dataset = load_dataset("dellacortelab/PANDA-PLUS-Bench", split="baseline") |
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# Access a sample |
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sample = dataset[0] |
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image = sample['image'] # PIL Image |
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label = sample['label'] # 0-3 |
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slide_id = sample['slide_id'] # Slide identifier |
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``` |
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## Evaluation |
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See our [Colab notebook](https://colab.research.google.com/github/dellacortelab/PANDA-PLUS-Bench/blob/main/PANDA_PLUS_Bench_Evaluation.ipynb) for standardized evaluation. |
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## Citation |
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```bibtex |
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@article{ebbert2025pandaplusbench, |
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title={PANDA-PLUS-Bench: A Benchmark for Evaluating WSI-Specific Feature Collapse}, |
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author={Ebbert, Joshua and Della Corte, Dennis}, |
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year={2025} |
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} |
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``` |
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## License |
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CC-BY-4.0 |
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