|
--- |
|
license: other |
|
language: |
|
- en |
|
tags: |
|
- biology |
|
- medical |
|
- cancer |
|
datasets: |
|
- owkin/nct-crc-he |
|
- owkin/camelyon16-features |
|
pipeline_tag: feature-extraction |
|
--- |
|
|
|
# Model Card for Phikon |
|
|
|
--- |
|
|
|
> [!IMPORTANT] |
|
> 🎉 Check out the latest version of Phikon here: [Phikon-v2](https://huggingface.co/owkin/phikon-v2) |
|
> |
|
> |
|
Phikon is a self-supervised learning model for histopathology trained with iBOT. |
|
|
|
To learn more about how to use the model, we encourage you to read our blog post and view this Colab notebook. |
|
|
|
### Model Description |
|
|
|
- **Developed by:** Owkin |
|
- **Funded by:** Owkin and IDRIS |
|
- **Model type:** Vision Transformer Base |
|
- **Model Stats:** |
|
- Params (M): 85.8 |
|
- Image size: 224 x 224 x 3 |
|
- **Paper:** |
|
- Scaling Self-Supervised Learning for Histopathology with Masked Image Modeling. A. Filiot et al., medRxiv 2023.07.21.23292757; doi: [https://doi.org/10.1101/2023.07.21.23292757](https://www.medrxiv.org/content/10.1101/2023.07.21.23292757v2) |
|
- **Pretrain Dataset:** 40 million pan-cancer tiles extracted from [TGCA](https://portal.gdc.cancer.gov/) |
|
- **Original:** https://github.com/owkin/HistoSSLscaling/ |
|
- **License:** [Owkin non-commercial license](https://github.com/owkin/HistoSSLscaling/blob/main/LICENSE.txt) |
|
|
|
## Uses |
|
|
|
### Direct Use |
|
|
|
The primary use of the Phikon model can be used for feature extraction from histology image tiles. |
|
|
|
### Downstream Use |
|
|
|
The model can be used for cancer classification on a variety of cancer subtypes. The model can also be finetuned to specialise on cancer subtypes. |
|
|
|
|
|
## Technical Specifications |
|
|
|
### Compute Infrastructure |
|
|
|
All the models we built were trained on the French Jean Zay cluster. |
|
|
|
### Hardware |
|
|
|
NVIDIA V100 GPUs with 32Gb RAM |
|
|
|
### Software |
|
|
|
PyTorch 1.13.1 |
|
|
|
--- |
|
|
|
### BibTeX entry and citation info |
|
|
|
```bibtex |
|
@article{Filiot2023ScalingSSLforHistoWithMIM, |
|
author = {Alexandre Filiot and Ridouane Ghermi and Antoine Olivier and Paul Jacob and Lucas Fidon and Alice Mac Kain and Charlie Saillard and Jean-Baptiste Schiratti}, |
|
title = {Scaling Self-Supervised Learning for Histopathology with Masked Image Modeling}, |
|
elocation-id = {2023.07.21.23292757}, |
|
year = {2023}, |
|
doi = {10.1101/2023.07.21.23292757}, |
|
publisher = {Cold Spring Harbor Laboratory Press}, |
|
url = {https://www.medrxiv.org/content/early/2023/07/26/2023.07.21.23292757}, |
|
eprint = {https://www.medrxiv.org/content/early/2023/07/26/2023.07.21.23292757.full.pdf}, |
|
journal = {medRxiv} |
|
} |
|
``` |
