Eswar1885/tcga-luad-provgigapath-embeddings
TCGA-LUAD — Prov-GigaPath Tile Embeddings Pre-extracted 1536-dimensional tile embeddings for TCGA-LUAD diagnostic H&E whole-slide images, produced with the Prov-GigaPath tile encoder (prov-gigapath/prov-gigapath). Part of a four-encoder benchmark in which every model was run on the identical tiles for a fair comparison. Tiling (identical across all encoders in the study) Source: raw TCGA-LUAD .svs (GDC, open-access diagnostic slides). 20× / 0.5 microns per pixel… See the full description on the dataset page: https://huggingface.co/datasets/Eswar1885/tcga-luad-provgigapath-embeddings.
TCGA-LUAD — Prov-GigaPath Tile Embeddings
Pre-extracted 1536-dimensional tile embeddings for TCGA-LUAD diagnostic H&E whole-slide images, produced with the Prov-GigaPath tile encoder (prov-gigapath/prov-gigapath). Part of a four-encoder benchmark in which every model was run on the identical tiles for a fair comparison.
Tiling (identical across all encoders in the study)
- Source: raw TCGA-LUAD
.svs(GDC, open-access diagnostic slides). - 20× / 0.5 microns per pixel, MPP-aware (handles mixed 20×/40× scans).
- 256 × 256 px tiles, non-overlapping, full tissue coverage (Otsu on HSV saturation).
- Prov-GigaPath's official transform (Resize 256 → CenterCrop 224 → ImageNet norm) applied per tile.
Format (per slide, CLAM-compatible)
<slide_id>.h5:
features—(N, 1536)float32coords—(N, 2)int32, level-0 (x, y) of each tile- attrs:
patch_size=256,patch_level=0,target_mpp=0.5,model,embed_dim
slide_id = TCGA barcode + GDC file UUID. Task labels (PDS / TP53 / EGFR / KRAS) are in labels/ (schema: case_id, slide_id, label).
Cohort
531 slides / 478 patients (diagnostic FFPE, primary tumor).
Attribution & license
- Source model: Prov-GigaPath — Xu et al., A whole-slide foundation model for digital pathology from real-world data, Nature 2024. Model under Apache-2.0.
- These derived embeddings are released under CC-BY-NC 4.0, honoring the model's research-only / non-clinical intent. Not for clinical use.
- Source images: TCGA-LUAD (NIH/GDC), open-access.
Provided for non-commercial academic research. Please cite the Prov-GigaPath paper and TCGA when using these features.
