H&E Patch Classification
Collection
Patch classification models for use with WSInfer. โข 10 items โข Updated โข 5
How to use kaczmarj/colorectal-tiatoolbox-resnet50.kather100k with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="kaczmarj/colorectal-tiatoolbox-resnet50.kather100k")
pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("kaczmarj/colorectal-tiatoolbox-resnet50.kather100k", device_map="auto")This is a re-hosted version of the model available in the TIA Toolbox model zoo (licensed CC-BY-4.0).
Coming soon...
The Kather100K dataset can be found on Zenodo https://zenodo.org/record/1214456.
@inproceedings{he2016deep,
title={Deep residual learning for image recognition},
author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
pages={770--778},
year={2016}
}
@dataset{kather_jakob_nikolas_2018_1214456,
author = {Kather, Jakob Nikolas and
Halama, Niels and
Marx, Alexander},
title = {{100,000 histological images of human colorectal
cancer and healthy tissue}},
month = apr,
year = 2018,
publisher = {Zenodo},
version = {v0.1},
doi = {10.5281/zenodo.1214456},
url = {https://doi.org/10.5281/zenodo.1214456}
}
@article{pocock2022tiatoolbox,
title={TIAToolbox as an end-to-end library for advanced tissue image analytics},
author={Pocock, Johnathan and Graham, Simon and Vu, Quoc Dang and Jahanifar, Mostafa and Deshpande, Srijay and Hadjigeorghiou, Giorgos and Shephard, Adam and Bashir, Raja Muhammad Saad and Bilal, Mohsin and Lu, Wenqi and others},
journal={Communications medicine},
volume={2},
number={1},
pages={120},
year={2022},
publisher={Nature Publishing Group UK London}
}