Models 11

This model is a feature extractor for CT-FM, a model pre-trained using contrastive self-supervised learning on a huge dataset of 148,000 CT…

This model is a SegResNet containing the weights of the pre-trained CT-FM, using contrastive self-supervised learning on a huge dataset of 1…

This section provides a quick start example for using the EndoViT model.

`H-optimus-0` is an open-source foundation model for histology, developed by Bioptimus. The model is a 1.1B parameter vision transformer tra…

Hibou-B - a Foundational Vision Transformer for digital pathology pretrained on a private dataset using DINOv2 framework.

Hibou-L - a Foundational Vision Transformer for digital pathology pretrained on a 1.2B image private dataset using DINOv2 framework.

M3D-CLIP is one of the works in the M3D series. It is a 3D medical CLIP model that aligns vision and language through contrastive loss on th…

[[`Code`]](https://github.com/prov-gigapath/prov-gigapath) [`Model`] [`Paper`] [`BibTeX`]

Virchow is a self-supervised vision transformer pretrained using 1.5M whole slide histopathology images. The model can be used as a tile-lev…