histocartography.ml.models.tissue_graph_model module

Summary

Classes:

TissueGraphModel

Tissue Graph Model.

class TissueGraphModel(gnn_params: Dict, classification_params: Dict, node_dim: int, **kwargs)

Bases: histocartography.ml.models.base_model.BaseModel

Tissue Graph Model. Apply a GNN on tissue level.

__init__(gnn_params: Dict, classification_params: Dict, node_dim: int, **kwargs)

TissueGraphModel model constructor.

Parameters

• gnn_params (Dict) – GNN configuration parameters.

• classification_params (Dict) – classification configuration parameters.

• node_dim (int) – Tissue node feature dimension.

forward(graph: Union[dgl.graph.DGLGraph, Tuple[None._VariableFunctions.tensor, None._VariableFunctions.tensor]]) → None._VariableFunctions.tensor

Foward pass.

Parameters

graph (Union[dgl.DGLGraph, Tuple[torch.tensor, torch.tensor]]) – Tissue graph to process.

Returns

Model output.

Return type

torch.tensor

set_lrp(with_lrp)

lrp(out_relevance_score)

Reference

If you use histocartography in your projects, please cite the following:

@inproceedings{pati2021,
    title = {Hierarchical Graph Representations for Digital Pathology},
    author = {Pushpak Pati, Guillaume Jaume, Antonio Foncubierta, Florinda Feroce, Anna Maria Anniciello, Giosuè Scognamiglio, Nadia Brancati, Maryse Fiche, Estelle Dubruc, Daniel Riccio, Maurizio Di Bonito, Giuseppe De Pietro, Gerardo Botti, Jean-Philippe Thiran, Maria Frucci, Orcun Goksel, Maria Gabrani},
    booktitle = {https://arxiv.org/pdf/2102.11057},
    year = {2021}
}