wolny/pytorch-3dunet
A PyTorch library providing 3D U-Net and residual variants for semantic segmentation of volumetric medical imaging data.
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This repository implements 3D U-Net architectures including standard, residual, and squeeze-and-excitation variants for volumetric semantic segmentation. It supports both binary and multi-class segmentation as well as regression tasks like de-noising. The models have been applied to connectomics and medical volume datasets, with configurations available for both 3D and 2D segmentation tasks.
Frequently asked
- What is wolny/pytorch-3dunet?
- A PyTorch library providing 3D U-Net and residual variants for semantic segmentation of volumetric medical imaging data.
- Is pytorch-3dunet open source?
- Yes — wolny/pytorch-3dunet is open source, released under the MIT license.
- What language is pytorch-3dunet written in?
- wolny/pytorch-3dunet is primarily written in Jupyter Notebook.
- How popular is pytorch-3dunet?
- wolny/pytorch-3dunet has 2.4k stars on GitHub.
- Where can I find pytorch-3dunet?
- wolny/pytorch-3dunet is on GitHub at https://github.com/wolny/pytorch-3dunet.