BRFound
A breast-specific slide-level foundation model for computational pathology. Implementation and preprocessing examples: wyh196646/BRFound.
Weights
| File | Contents |
|---|---|
patch_encoder.pth |
Released BRFound patch encoder |
slide_encoder.pth |
Original epoch-161 slide training checkpoint |
slide_encoder_inference.pth |
Plain state dictionary of the same teacher backbone |
inference_config.json |
Epoch, dimensions and checkpoint checksums |
The October 2026 update adds a compact inference export and the current overview. The numerical model parameters are unchanged. The existing patch and training weights are retained for compatibility.
Slide embedding
Use the repository's inference.py with slide_encoder_inference.pth. Input is an HDF5
file containing BRFound patch features of shape [N, 768] and matching coords of
shape [N, 2] on the training pipeline's 256-pixel coordinate grid.
python inference.py --features features.h5 --weights slide_encoder_inference.pth --output slide_embedding.npy --device cpu
The output has shape [1, 768]. The default sampler uses eight clusters, a 25% ratio,
a 4,000-token cap and seed 42. Full usage and preprocessing instructions are in the
code repository.
These are research representations; downstream clinical use requires task-specific validation. The release checks cover CPU inference and equivalence of the compact weights and positional encoding to the original implementation.