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license: cc-by-nc-sa-4.0 |
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--- |
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# CAMELYON16 patch embeddings made with UNI |
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This repository contains patch embeddings for CAMELYON16 made with the UNI foundation model. |
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Patches are 128x128 micrometers. Tissue segmentation and patching was done with a modified version of the CLAM toolkit. |
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The toolkit was modified to extract constant physical size patches. |
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The `patches` directory contains HDF5 files with patch coordinates. The attribute `patch_size` on the `/coords` dataset |
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contains the patch size in pixels. This is equivalent to the physical size of 128 micrometers. |
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The `embeddings` directory contains PyTorch files with embeddings. Each specimen in CAMELYON16 is in a separate file, |
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and each file contains a 2D tensor of shape `(n_patches, n_features)`. The value of `n_patches` can differ across specimens. |
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The order of the patches is the same between the patch HDF5 file and the features PyTorch file. |
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# Intended use cases |
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This dataset is intended for training weakly-supervised neural networks on CAMELYON16. |
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It is also intended to help others reproduce the experiments in the HIPPO manuscript. |
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# Links |
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- CAMELYON16: https://camelyon16.grand-challenge.org/ |
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- CLAM: https://github.com/mahmoodlab/CLAM |
