stlearn.pp.extract_feature

stlearn.pp.extract_feature(adata: AnnData, cnn_base: Literal['resnet50', 'vgg16', 'inception_v3', 'xception'] = 'resnet50', n_components: int = 50, seeds: int = 1, verbose: bool = False, copy: bool = False) → AnnData | None

Extract latent morphological features from H&E images using pre-trained convolutional neural network base

Parameters:

• adata – Annotated data matrix.

• cnn_base – Established convolutional neural network bases choose one from [‘resnet50’, ‘vgg16’, ‘inception_v3’, ‘xception’]

• n_components – Number of principal components to compute for latent morphological features

• seeds – Fix random state

• verbose – Verbose output

• copy – Return a copy instead of writing to adata.

Returns:

• Depending on copy, returns or updates adata with the following fields.

• **X_morphology** (adata.obsm field) – Dimension reduced latent morphological features.

Raises:

ValueError – If any image fails to process or if tile_path column is missing.