| Models | |
| ====== | |
| ``PathML`` comes with model architectures ready to use out of the box. | |
| .. table:: | |
| :widths: 20, 20, 60 | |
| ============================================ ============ ============= | |
| Model Reference Description | |
| ============================================ ============ ============= | |
| :class:`~pathml.ml.models.hovernet.HoVerNet` [HoVerNet]_ A model for nucleus segmentation and classification in H&E images | |
| :class:`~pathml.ml.models.hactnet.HACTNet` [HACTNet]_ A graph neural network (GNN) for cancer subtyping | |
| ============================================ ============ ============= | |
| You can also use models from fantastic resources such as | |
| `torchvision.models <https://pytorch.org/docs/stable/torchvision/models.html>`_ and | |
| `pytorch-image-models (timm) <https://rwightman.github.io/pytorch-image-models/>`_. | |
| 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. |