Tools: tl#

Image Embedding#

tl.feature_extraction

Extract features from WSI tiles using a pre-trained vision models.

tl.feature_aggregation

Aggregate features by groups.

tl.spatial_features

Integrate spatial tile context with vision features using spatial feature smoothing.

Tissue/Tile Properties#

tl.tissue_props

Compute a series of geometrical properties of tissue piecies

tl.tile_prediction

Predict tiles using a tile prediction model.

Tissue Spatial Domain#

tl.spatial_domain

Perform unsupervised spatial domain segmentation on a WSI using feature embeddings.

tl.tile_shaper

Return the domain shapes of the WSI by merging tiles with the same types that are spatially aggregated into polygons using geopandas dissolve.

Multi-Modal Analysis#

tl.text_embedding

Embed the text into a vector in the text-vision co-embedding using

tl.text_image_similarity

Compute the similarity between text and image.

tl.RNALinker

Link the aggregated WSI features with other omics data.

Zero-shot Learning#

tl.zero_shot_score

Perform zero-shot classification on the WSI

tl.slide_caption

Generate captions for the slide.

Virtual staining#

tl.virtual_stain

Translate the HE images to multiplexed images.