Skip to main content

RadQy is a quality assurance and checking tool for quantitative assessment of magnetic resonance imaging (MRI) and computed tomography (CT) data.

Project description

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).

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

radqy-2025.3.2.tar.gz (17.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

radqy-2025.3.2-py3-none-any.whl (18.2 kB view details)

Uploaded Python 3

File details

Details for the file radqy-2025.3.2.tar.gz.

File metadata

  • Download URL: radqy-2025.3.2.tar.gz
  • Upload date:
  • Size: 17.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.20

File hashes

Hashes for radqy-2025.3.2.tar.gz
Algorithm Hash digest
SHA256 3b2879a1f803461c588bc9638870e99ca0efddfcbe7c731593845c6c10b01f0e
MD5 18f83026aaddece4cc658e5afb1b6d2f
BLAKE2b-256 a4bcd35d626ff6398fed58030cfaf8a2cd0d6804810f4b4d0c94e8ce20fe05b2

See more details on using hashes here.

File details

Details for the file radqy-2025.3.2-py3-none-any.whl.

File metadata

  • Download URL: radqy-2025.3.2-py3-none-any.whl
  • Upload date:
  • Size: 18.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.20

File hashes

Hashes for radqy-2025.3.2-py3-none-any.whl
Algorithm Hash digest
SHA256 ae4bd7010464f53f71bc0dd5446e05c1925c6cc543b6f18071f049b70dfc01a6
MD5 b57a3d042ae2ff1cbbab16dbea81152c
BLAKE2b-256 edc8c49c679333ec145b9e9141f400eaecd73c77ac36a92aeb9cfc44f22944d5

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page