A package to extract radiomic features!
Project description
READII
Radiomic Extraction and Analysis for DICOM Images
A package to extract radiomic features from DICOM CT images.
Installation
$ pip install readii
(recommended) Create new conda virtual environment
conda create -n readii python=3.9
conda activate readii
pip install readii
Usage
readii
is a tool to perform radiomic feature extraction on DICOM CT images with region of interest (ROI) segmentations as either DICOM SEG or RTSTRUCT.
$ readii [INPUT DIRECTORY] [OUTPUT DIRECTORY] \
--roi_names [str] \
--pyradiomics_setting [str] \
--negative_controls [str: randomized_full,randomized_roi,randomized_non_roi,shuffled_full,shuffled_roi,shuffled_non_roi] \
--parallel [flag]
--update [flag]
Contributing
Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.
License
readii
was created by Katy Scott. It is licensed under the terms of the MIT license.
Credits
readii
was created with cookiecutter
and the py-pkgs-cookiecutter
template.
Project details
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