CellDetection 0.3.1

Cell Detection with PyTorch.

Cell Detection

⭐ Showcase

Nuclei of U2OS cells in a chemical screen

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

P. vivax (malaria) infected human blood

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.

• Train your own model
• Train a model with multiple object classes

🔬 Models

import celldetection as cd

Contour Proposal Networks

• cd.models.CPN
• cd.models.CpnU22
• cd.models.CpnSlimU22
• cd.models.CpnResUNet
• cd.models.CpnWideU22
• cd.models.CpnResNet34FPN
• cd.models.CpnResNet50FPN
• cd.models.CpnResNet18FPN
• cd.models.CpnResNeXt50FPN
• cd.models.CpnResNet101FPN
• cd.models.CpnResNet152FPN
• cd.models.CpnResNeXt101FPN
• cd.models.CpnResNeXt152FPN
• cd.models.CpnWideResNet50FPN
• cd.models.CpnWideResNet101FPN
• cd.models.CpnMobileNetV3SmallFPN
• cd.models.CpnMobileNetV3LargeFPN

U-Nets

• cd.models.U22
• cd.models.U17
• cd.models.U12
• cd.models.UNet
• cd.models.WideU22
• cd.models.SlimU22
• cd.models.ResUNet
• cd.models.UNetEncoder
• cd.models.ResNet50UNet
• cd.models.ResNet18UNet
• cd.models.ResNet34UNet
• cd.models.ResNet152UNet
• cd.models.ResNet101UNet
• cd.models.ResNeXt50UNet
• cd.models.ResNeXt152UNet
• cd.models.ResNeXt101UNet
• cd.models.WideResNet50UNet
• cd.models.WideResNet101UNet
• cd.models.MobileNetV3SmallUNet
• cd.models.MobileNetV3LargeUNet

Feature Pyramid Networks

• cd.models.FPN
• cd.models.ResNet18FPN
• cd.models.ResNet34FPN
• cd.models.ResNet50FPN
• cd.models.ResNeXt50FPN
• cd.models.ResNet101FPN
• cd.models.ResNet152FPN
• cd.models.ResNeXt101FPN
• cd.models.ResNeXt152FPN
• cd.models.WideResNet50FPN
• cd.models.WideResNet101FPN
• cd.models.MobileNetV3LargeFPN
• cd.models.MobileNetV3SmallFPN

Residual Networks

• cd.models.ResNet18
• cd.models.ResNet34
• cd.models.ResNet50
• cd.models.ResNet101
• cd.models.ResNet152
• cd.models.WideResNet50_2
• cd.models.ResNeXt50_32x4d
• cd.models.WideResNet101_2
• cd.models.ResNeXt101_32x8d
• cd.models.ResNeXt152_32x8d

Mobile Networks

• cd.models.MobileNetV3Large
• cd.models.MobileNetV3Small

📝 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

• Article (sciencedirect)
• PDF (sciencedirect)
• Abstract (arXiv)
• PyPI
• Documentation