Published May 6, 2020 | Version 1.0
Software Open

Pretrained 3D U-Net models for COVID-19 CT Lung and Infection Segmentation

  • 1. Department of Mathematics, Nanjing University of Science and Technology
  • 2. Institute of Computing Technology, Chinese Academy of Sciences;University of Chinese Academy of Sciences
  • 3. China Electronics Cloud Brain (Tianjin) Technology CO., LTD
  • 4. Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology
  • 5. Institute of Science and Technology for Brain-inspired Intelligence, Fudan University

Description

We provide 45 trained 3D U-Net baseline models for COVID-19 CT Lung and Infection Segmentation benchmark (https://gitee.com/junma11/COVID-19-CT-Seg-Benchmark).

The implementation is based on nnU-Net that is an out-of-the-box segmentation tool for 3D biomedical image data. 

Instructions for how to use the models are provided at https://github.com/MIC-DKFZ/nnUNet

Ground truth can be download at http://doi.org/10.5281/zenodo.3757476

Files

Task100_COVIDLung.zip

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Additional details

Related works

Cites
Software: https://gitee.com/junma11/COVID-19-CT-Seg-Benchmark (URL)
Dataset: 10.5281/zenodo.3757476 (DOI)
Is documented by
Software documentation: https://github.com/MIC-DKFZ/nnUNet (URL)