All Projects → FZJ-INM1-BDA → celldetection

FZJ-INM1-BDA / celldetection

Licence: Apache-2.0 license
Cell Detection with PyTorch.

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python
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Cell Detection

Downloads Test PyPI Documentation Status

Showcase

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

💡 How to train

Here you can see some examples of how to train a detection model. The examples already include toy data, so you can get started right away.

🔬 Models

import celldetection as cd

Contour Proposal Networks
U-Nets
Feature Pyramid Networks
Residual Networks
Mobile Networks

📝 Citing

@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

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