MahmoodLab/SEAL
Updated
• 9
Weiyi Qin
W8Yi
·
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Recent Activity
posted an
update
about 7 hours ago
I built a **TCGA WSI feature dataset using UNI2-h**.
The official release currently has incomplete coverage (see discussion):
https://huggingface.co/datasets/MahmoodLab/UNI2-h-features/discussions/2#681b5ed184d0a008fca99297
To make the features easier to use for research, I generated a new dataset:
https://huggingface.co/datasets/W8Yi/tcga-wsi-uni2h-features
Key differences from the official release:
• **All detected tissue tiles are encoded** (not a sampled subset)
• **Features can be downloaded per slide** instead of large ZIP archives
• **QC overlay images** are provided for visual inspection
• **UNI2-h 1536-D tile embeddings** stored in H5 format
• Organized by TCGA project for easier use in MIL / retrieval pipelines
Example layout:
```
TCGA-HNSC/
features/*.h5
vis/*__overlay.png
```
Hope this helps others working on computational pathology and TCGA WSI research.
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