Published May 31, 2020
| Version 1.0
Software
Open
Pretrained 2D U-Net models for COVID-19 CT Lung and Infection Segmentation
Creators
- 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 2D 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
01_Task1_Prediction.zip
Files
(14.3 GB)
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Additional details
Related works
- Cites
- 10.5281/zenodo.3757476 (DOI)
- Is documented by
- Software: https://github.com/MIC-DKFZ/nnUNet (URL)
- Is supplemented by
- https://gitee.com/junma11/COVID-19-CT-Seg-Benchmark (URL)