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End of preview. Expand
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Dataset Card for Histopathology Dataset
Dataset Summary
This dataset contains 224x224, 512x512 and 1024x1024 patches of a group of histopathology images taken from the CAMELYON16 dataset and embedding vectors extracted from these patches using the Google Path Foundation model.
Thumbnail of Main Slide
Usage
from datasets import load_dataset
dataset = load_dataset("Cilem/histopathology")
display(dataset['train'][0]["image"])
Supported Tasks
Machine learning applications that can be performed using this dataset:
- Classification
- Segmentation
- Image generation
Languages
- English
Dataset Structure
Data Fields
image: Image of the patch.slide_name: Main slide name of the patch.x: X coordinate of the patch.y: Y coordinate of the patch.level: Level of the main slide.patch_size: Size of the patch.resize: Image size used to obtain embedding vector with Path foundation model.embedding_vector: Embedding vector of the patch extracted using Path foundation model.
Dataset Creation
Source Data
- Original Sources
- CAMELYON16: List of images taken from CAMELYON16 dataset:
test_001.tiftest_002.tiftest_003.tiftest_004.tiftest_005.tiftest_006.tiftest_007.tiftest_008.tiftest_009.tif
- Google Path Foundation: Embedding vectors extracted from the patches using the Path Foundation model.
- CAMELYON16: List of images taken from CAMELYON16 dataset:
Considerations for Using the Data
Social Impact and Bias
Attention should be paid to the Path Foundation model licenses provided by Google.
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