CellDetection

Eric Upschulte

doi:10.5281/zenodo.8286160

CellDetection

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.

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410 commitsLast commit ≈ 8 months ago145 stars21 forks

Description

Cell Detection

⭐ Showcase

🛠 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 name	training data	link
`ginoro_CpnResNeXt101UNet-fbe875f1a3e5ce2c`	BBBC039, 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

NeurIPS 2022 Cell Segmentation Challenge: Winner Finalist Award

📝 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},
}