Metadata-Version: 2.4
Name: radqy
Version: 2025.3.2
Summary: RadQy is a quality assurance and checking tool for quantitative assessment of magnetic resonance imaging (MRI) and computed tomography (CT) data.
Author-email: Amir Reza Sadri <ars329@case.edu>
License: BSD 3-Clause Clear License
Keywords: MRI,CT
Classifier: Programming Language :: Python :: 3.8
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Requires-Python: <3.12,>=3.8
Description-Content-Type: text/x-rst
Requires-Dist: importlib-metadata; python_version < "3.8"
Requires-Dist: numpy>=1.23.1
Requires-Dist: medpy>=0.4.0
Requires-Dist: matplotlib>=3.5.1
Requires-Dist: pydicom>=2.3.0
Requires-Dist: pandas>=1.4.2
Requires-Dist: scipy>=1.8.0
Requires-Dist: scikit-learn>=1.0.2
Requires-Dist: scikit-image>=0.19.2
Requires-Dist: umap-learn>=0.5.3
Requires-Dist: pyyaml>=6.0.1
Requires-Dist: requests>=2.32.3

RadQy
=====

RadQy is a quality assurance and evaluation tool for quantitative assessment of MRI and CT imaging data.

It computes a variety of image quality metrics (IQMs) to assist with downstream image analysis, machine learning, and radiomic studies.

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Features:
- Computes over 30 image quality metrics
- Supports T1w, T2w, and CT modalities
- UMAP visualization of quality trends
- CLI for batch processing

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Installation
------------

From GitHub (latest version):
::

    pip install git+https://github.com/viswanath-lab/RadQy.git

From PyPI (stable, may lag behind):
::

    pip install radqy

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Usage
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Run from command line:

::

    radqy --modality T1w --input my_scan.nii.gz

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Citation
--------

If you use this software, please cite the corresponding paper (coming soon).
