U-Net Architecture

The U-Net architecture achieves very good performance on very different biomedical segmentation applications. U-net architecture (example for 32x32 pixels in the lowest resolution) as presented in Figure 1. Each blue box corresponds to a multi-channel feature map. The number of channels is denoted on top of the box. The x-y-size is provided at the lower left edge of the box. White boxes represent copied feature maps. The arrows denote the different operations. This work is based on Ronneberger et al.

HOW TO INSTALL

conda create -n torch python==3.9
conda activate torch

git clone https://github.com/brain-facens/u-net-template.git
cd u-net-template
pip install -r requirement.txt

You can find the notebook in ./notebooks/UNet_seg.ipynb.

🤝 Collaborators

We would like to thank the following people who contributed to this project:

Natanael Vitorino

📝 License

This project is under license. See the file LICENSE for more details.

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