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waticlems/slide2vec

By waticlems

•Updated 1 day ago

Encoding whole-slide images into features using publicly available foundation models

Image
Machine learning & AI
0

8.6K

waticlems/slide2vec repository overview

Encoding whole-slide images into features using publicly available foundation models.
Depending on your use case, whole-slide images can be encoded into one of the following 3 features:

1- tile-level: (N, feature_dim) where N is the number of tiles of a specific size at a specific spacing
2- region-level: (M, n, feature_dim) where M is the number of regions of a specific size at a specific spacing, and n the number of non-overlapping tiles that can be extracted from each region
3- slide-level: (1, feature_dim)

List of foundation models currently supported: UNI, UNI-2, Virchow, Virchow2, H-optimus-0, H-optimus-1, Prov-GigaPath (use the gigapath tag), TITAN (use the titan tag), PRISM (use the prism tag)

Tag summary

Content type

Image

Digest

sha256:25b0e460a…

Size

7.6 GB

Last updated

1 day ago

docker pull waticlems/slide2vec