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crip

★ 55 Open GitHub ↗

CT Recon in Python: An all-in-one tool for Data IO, Pre/Post-process, Physics, Dual Energy, Low Dose and everything.

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CT Recon in Python (crip) is an All-in-one toolkit for CT Data IO, Pre/Post-process, Physics, Dual Energy, Low Dose and everything.

:warning: crip is still under very "agile" development and **no** API consistency and correctness validation between versions are guaranteed. Use at your own risk! :construction:

## Install

[![Upload Python Package](https://github.com/SEU-CT-Recon/crip/actions/workflows/python-publish.yml/badge.svg)](https://github.com/SEU-CT-Recon/crip/actions/workflows/python-publish.yml)

```sh
pip install crip
```

## Documentation

- [Official Documentation](https://seu-ct-recon.github.io/crip)
- [Unit Test Coverage](https://seu-ct-recon.github.io/crip/htmlcov)
- [Jupyter Notebook Examples](https://github.com/SEU-CT-Recon/crip/tree/master/example)
- Ask everything in [issue](https://github.com/SEU-CT-Recon/crip/issues).

## License

MIT

## Cite This

```
@software{crip,
  author = {SEU-CT-Recon},
  license = {MIT},
  title = {{crip}},
  url = {https://github.com/SEU-CT-Recon/crip}
}
```

crip

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