Name | radqy JSON |
Version |
2025.3.2
JSON |
| download |
home_page | None |
Summary | RadQy is a quality assurance and checking tool for quantitative assessment of magnetic resonance imaging (MRI) and computed tomography (CT) data. |
upload_time | 2025-07-31 14:04:00 |
maintainer | None |
docs_url | None |
author | None |
requires_python | <3.12,>=3.8 |
license | BSD 3-Clause Clear License |
keywords |
mri
ct
|
VCS |
|
bugtrack_url |
|
requirements |
No requirements were recorded.
|
Travis-CI |
No Travis.
|
coveralls test coverage |
No coveralls.
|
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.
----
Features:
- Computes over 30 image quality metrics
- Supports T1w, T2w, and CT modalities
- UMAP visualization of quality trends
- CLI for batch processing
----
Installation
------------
From GitHub (latest version):
::
pip install git+https://github.com/viswanath-lab/RadQy.git
From PyPI (stable, may lag behind):
::
pip install radqy
----
Usage
-----
Run from command line:
::
radqy --modality T1w --input my_scan.nii.gz
----
Citation
--------
If you use this software, please cite the corresponding paper (coming soon).
Raw data
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