An open-source Python package, offering advanced AI methods for the identification and segmentation of biomedical objects, such as cells, in image data. Includes trained models that work out-of-the-box for a wide range of use cases.
https://openreview.net/forum?id=YtgRjBw-7GJ
https://bbbc.broadinstitute.org/BBBC039 (CC0)
https://bbbc.broadinstitute.org/BBBC041 (CC BY-NC-SA 3.0)
Make sure you have PyTorch installed.
pip install -U celldetection
pip install git+https://github.com/FZJ-INM1-BDA/celldetection.git
model = cd.fetch_model(model_name, check_hash=True)
model name | training data | link |
---|---|---|
ginoro_CpnResNeXt101UNet-fbe875f1a3e5ce2c | BBBC039, BBBC038, Omnipose, Cellpose, Sartorius - Cell Instance Segmentation, Livecell, NeurIPS 22 CellSeg Challenge | 🔗 |
Find us on Docker Hub: https://hub.docker.com/r/ericup/celldetection
You can pull the latest version of celldetection
via:
doker pull ericup/celldetection:latest
You can also pull our Docker images for the use with Apptainer (formerly Singularity) with this command:
apptainer pull --dir . --disable-cache docker://ericup/celldetection:latest
Find us on Hugging Face and upload your own images for segmentation: https://huggingface.co/spaces/ericup/celldetection
Find our Napari Plugin here: https://github.com/FZJ-INM1-BDA/celldetection-napari
Find out more about Napari here: https://napari.org
You can install it via pip:
pip install git+https://github.com/FZJ-INM1-BDA/celldetection-napari.git
If you find this work useful, please consider giving a star ⭐️ and citation:
@article{UPSCHULTE2022102371,
title = {Contour proposal networks for biomedical instance segmentation},
journal = {Medical Image Analysis},
volume = {77},
pages = {102371},
year = {2022},
issn = {1361-8415},
doi = {https://doi.org/10.1016/j.media.2022.102371},
url = {https://www.sciencedirect.com/science/article/pii/S136184152200024X},
author = {Eric Upschulte and Stefan Harmeling and Katrin Amunts and Timo Dickscheid},
keywords = {Cell detection, Cell segmentation, Object detection, CPN},
}