Models

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

Model

Reference

Description

U-net (in progress)

[Unet]

A model for segmentation in biomedical images

HoVerNet

[HoVerNet]

A model for nucleus segmentation and classification in H&E images

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

References

Unet

Ronneberger, O., Fischer, P. and Brox, T., 2015, October. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention (pp. 234-241). Springer, Cham.

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.