Metadata-Version: 2.4
Name: pyconvert
Version: 0.0.1
Summary: PyConveRT: convert radiotherapy treatment data between clinical (DICOM/NIfTI) conventions and ML-ready formats. Early release with a small working subset of coordinate and dose-unit conversions; the full pipeline is under active development.
Author-email: Matthias Kronsteiner <matthias.kronsteiner@meduniwien.ac.at>
License: MIT
Project-URL: Homepage, https://github.com/muw-airo/rt_ai_preprocessing
Keywords: radiotherapy,dicom,nifti,conversion,medical-imaging
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Requires-Python: >=3.11
Description-Content-Type: text/markdown

# PyConveRT

Convert radiotherapy treatment data between clinical conventions (DICOM / NIfTI)
and machine-learning-ready formats.

**Early release (0.0.1, pre-alpha).** This version ships a small, working subset of
the conversion helpers; the full DICOM/NIfTI preprocessing pipeline is under active
development. Developed alongside the companion project PyDoseRT.

## Installed and working now

```python
import pyconvert

pyconvert.lps_to_ras((10.0, 20.0, 30.0))   # -> (-10.0, -20.0, 30.0)   DICOM LPS -> NIfTI RAS
pyconvert.ras_to_lps((-10.0, -20.0, 30.0)) # -> (10.0, 20.0, 30.0)     NIfTI RAS -> DICOM LPS
pyconvert.gy_to_cgy(2.0)                    # -> 200.0                  gray -> centigray
pyconvert.cgy_to_gy(200.0)                  # -> 2.0                    centigray -> gray
```

Homepage: https://github.com/muw-airo/rt_ai_preprocessing
