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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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An all-in-one tool for Cone-Beam CT Data IO, Pre/Post-process, Physics, Dual Energy, Low Dose and everything only except Reconstruction.

⚠️ crip is still under very "agile" development and no API consistency between versions are guaranteed. Use at your own risk! 🚧

Install

  • Via PyPI

    Upload Python Package

    pip install crip
  • Via Wheel

    Download the latest release from Releases. Install the wheel by

    pip install /path/to/latest/release.whl

Modules

All functions are (or will be) with clear documentation. Just consider the function name and explore the source code, or refer to examples to start.

  • crip.de for Dual-Energy CT.
  • crip.io for file read/write (RAW, DICOM and TIFF supported).
  • crip.physics for attenuation, spectrum, coefficient calculation, etc.
  • crip.postprocess for data post-processing.
  • crip.preprocess for data pre-processing.
  • crip.shared for other common operations.
  • crip.lowdose for Low-Dose researches.
  • crip.mangoct for mangoct reconstruction tool package integration.
  • crip.metric for metrics computation.
  • crip.plot for figure drawing.

crip is still under development. More features will be added in the future. And contributions are strongly welcomed.

Documentation and Example

The Official documentation, and Official example. Ask everything in issue.

License

MIT

Cite This

@software{ZHUO_crip,
  author = {ZHUO, Xu and LU, Yuchen and SEU-CT-Recon},
  license = {MIT},
  title = {{crip}},
  url = {https://github.com/SEU-CT-Recon/crip}
}

We appreciate if you let us know you are using crip in your workflow or publications.

We are considering publishing crip to Journal of Open Source Software and/or apply for a Software Copyright in China in the future.

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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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