Metadata-Version: 2.4
Name: mircat-v2
Version: 0.3.1
Summary: Add your description here
License-File: LICENSE
Requires-Python: >=3.11
Requires-Dist: loguru>=0.7.3
Requires-Dist: numpy<2.0
Requires-Dist: threadpoolctl>=3.6.0
Provides-Extra: all
Requires-Dist: dicom2nifti>=2.6.1; extra == 'all'
Requires-Dist: kimimaro>=5.3.0; extra == 'all'
Requires-Dist: nibabel>=5.3.2; extra == 'all'
Requires-Dist: nnunetv2>=2.6.0; extra == 'all'
Requires-Dist: posix-ipc>=1.2.0; extra == 'all'
Requires-Dist: pydicom>=3.0.1; extra == 'all'
Requires-Dist: scikit-image>=0.25.2; extra == 'all'
Requires-Dist: simpleitk>=2.5.0; extra == 'all'
Requires-Dist: torch>=2.7.0; extra == 'all'
Requires-Dist: xgboost==2.0.3; extra == 'all'
Requires-Dist: xs3d>=1.10.0; extra == 'all'
Provides-Extra: dicom
Requires-Dist: dicom2nifti>=2.6.1; extra == 'dicom'
Requires-Dist: pydicom>=3.0.1; extra == 'dicom'
Provides-Extra: seg
Requires-Dist: nibabel>=5.3.2; extra == 'seg'
Requires-Dist: nnunetv2>=2.6.0; extra == 'seg'
Requires-Dist: torch>=2.7.0; extra == 'seg'
Provides-Extra: stats
Requires-Dist: kimimaro>=5.3.0; extra == 'stats'
Requires-Dist: nibabel>=5.3.2; extra == 'stats'
Requires-Dist: posix-ipc>=1.2.0; extra == 'stats'
Requires-Dist: scikit-image>=0.25.2; extra == 'stats'
Requires-Dist: simpleitk>=2.5.0; extra == 'stats'
Requires-Dist: xgboost==2.0.3; extra == 'stats'
Requires-Dist: xs3d>=1.10.0; extra == 'stats'
Description-Content-Type: text/markdown

# MirCAT-v2
Mirshahi-Lab CT Analysis Toolkit (MirCAT). Convert dicoms, segment niftis, extract data.  
V1 has been archived. This version is almost a full rewrite of the segmentation section, specifically to incorporate nnUNet models directly into the pipeline.


# NOTES
When using docker -> make sure to add the --ipc=host flag or segmentation will not work