Metadata-Version: 2.4
Name: pytorch-rdc-net
Version: 0.1.0
Summary: PyTorch implementation of the RDC-Net for 2D and 3D instance segmentation.
Project-URL: Bug Tracker, https://github.com/fmi-faim/pytorch-rdc-net/issues
Project-URL: Documentation, https://github.com/fmi-faim/pytorch-rdc-net#README.md
Project-URL: Homepage, https://github.com/fmi-faim/pytorch-rdc-net.git
Project-URL: Source Code, https://github.com/fmi-faim/pytorch-rdc-net
Project-URL: User Support, https://github.com/fmi-faim/pytorch-rdc-net/issues
Author-email: Tim-Oliver Buchholz <tim-oliver.buchholz@fmi.ch>
License-Expression: BSD-3-Clause
License-File: LICENSE
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Python: >=3.11
Requires-Dist: lightning
Requires-Dist: pytorch-ignite
Requires-Dist: torch
Requires-Dist: torchist
Description-Content-Type: text/markdown

# PyTorch RDC-Net

This is a PyTorch implementation of the [RDC-Net](https://github.com/fmi-basel/RDCNet) for instance segmentation of 2D and 3D images. Some demo training scripts can be found [here](https://github.com/fmi-faim/faim_rdcnet).


## Citation
If you find this work useful, please consider citing:

```bibtex
@inproceedings{ortiz2020,
  title={RDCNet: Instance segmentation with a minimalist recurrent residual network},
  author={Ortiz, Raphael and de Medeiros, Gustavo and Peters H.F.M., Antoine and Liberali, Prisca and Rempfler, Markus},
  booktitle={International Workshop on Machine Learning in Medical Imaging},
  year={2020},
}
```
