CellDetection

Authors: Eric Upschulte

Keywords: Image processing, Information, Data analysis, Modeling, Supercomputing, Open source, Deep learning, Cell segmentation, Cell detection, Instance segmentation, Cell counting, Pytorch

Cell Detection



Downloads Test PyPI Documentation Status DOI



⭐ Showcase


NeurIPS 22 Cell Segmentation Competition

neurips22

https://openreview.net/forum?id=YtgRjBw-7GJ


Nuclei of U2OS cells in a chemical screen

bbbc039

https://bbbc.broadinstitute.org/BBBC039 (CC0)


P. vivax (malaria) infected human blood

bbbc041

https://bbbc.broadinstitute.org/BBBC041 (CC BY-NC-SA 3.0)


🛠 Install


Make sure you have PyTorch installed.


PyPI


pip install -U celldetection

GitHub


pip install git+https://github.com/FZJ-INM1-BDA/celldetection.git

💾 Trained models


model = cd.fetch_model(model_name, check_hash=True)
















model nametraining datalink
ginoro_CpnResNeXt101UNet-fbe875f1a3e5ce2cBBBC039, BBBC038, Omnipose, Cellpose, Sartorius - Cell Instance Segmentation, Livecell, NeurIPS 22 CellSeg Challenge🔗

🐳 Docker


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

Apptainer


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

🤗 Hugging Face Spaces


Find us on Hugging Face and upload your own images for segmentation: https://huggingface.co/spaces/ericup/celldetection


🧑‍💻 Napari Plugin


Find our Napari Plugin here: https://github.com/FZJ-INM1-BDA/celldetection-napari


Find out more about Napari here: https://napari.org

bbbc039

You can install it via pip:


pip install git+https://github.com/FZJ-INM1-BDA/celldetection-napari.git

🏆 Awards



📝 Citing


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},
}

🔗 Links




Publications

The multimodality cell segmentation challenge: toward universal solutions

Ma J, Xie R, Ayyadhury S, Ge C, Gupta A, Gupta R, Gu S, Zhang Y, Lee G, Kim J, Lou W, Li H, Upschulte E, Dickscheid T, de Almeida J, Wang Y, Han L, Yang X, Labagnara M, Gligorovski V, Scheder M, Rahi S, Kempster C, Pollitt A, Espinosa L, Mignot T, Middeke J, Eckardt J, Li W, Li Z, Cai X, Bai B, Greenwald N, Van Valen D, Weisbart E, Cimini B, Cheung T, Brück O, Bader G, Wang B - Nature Methods - 2024


CellDetection

Upschulte E, Harmeling S, Amunts K, Dickscheid T - Zenodo - 2023


Contour proposal networks for biomedical instance segmentation

Upschulte E, Harmeling S, Amunts K, Dickscheid T - Medical Image Analysis - 2022


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