Models

PathML comes with model architectures ready to use out of the box.

Model	Reference	Description
HoVerNet	[HoVerNet]	A model for nucleus segmentation and classification in H&E images
HACTNet	[HACTNet]	A graph neural network (GNN) for cancer subtyping

You can also use models from fantastic resources such as torchvision.models and pytorch-image-models (timm).

References

[HoVerNet]

Graham, S., Vu, Q.D., Raza, S.E.A., Azam, A., Tsang, Y.W., Kwak, J.T. and Rajpoot, N., 2019. Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images. Medical Image Analysis, 58, p.101563.

[HACTNet]

Pati, P., Jaume, G., Foncubierta-Rodriguez, A., Feroce, F., Anniciello, A.M., Scognamiglio, G., Brancati, N., Fiche, M., Dubruc, E., Riccio, D. and Di Bonito, M., 2022. Hierarchical graph representations in digital pathology. Medical image analysis, 75, p.102264.