https://github.com/Open-Minds-Lab/mrQA

mrQA: tools for quality assurance in medical imaging datasets, including protocol compliance
https://github.com/Open-Minds-Lab/mrQA

brain ismrm mr-image mri mri-brain mri-images neuroimaging neuroscience niqc qa quality-assurance quality-control

Last synced: about 2 months ago
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mrQA: tools for quality assurance in medical imaging datasets, including protocol compliance

• Host: GitHub
• URL: https://github.com/Open-Minds-Lab/mrQA
• Owner: Open-Minds-Lab
• License: apache-2.0
• Created: 2022-01-04T21:06:27.000Z (almost 3 years ago)
• Default Branch: master
• Last Pushed: 2024-05-08T20:14:18.000Z (7 months ago)
• Last Synced: 2024-10-12T02:25:14.591Z (2 months ago)
• Topics: brain, ismrm, mr-image, mri, mri-brain, mri-images, neuroimaging, neuroscience, niqc, qa, quality-assurance, quality-control
• Language: Python
• Homepage: https://open-minds-lab.github.io/mrQA/
• Size: 16 MB
• Stars: 9
• Watchers: 3
• Forks: 6
• Open Issues: 38
• Metadata Files:
  • Readme: README.rst
  • Changelog: HISTORY.rst
  • Contributing: CONTRIBUTING.rst
  • License: LICENSE
  • Authors: AUTHORS.rst

Awesome Lists containing this project

• awesome-neuroimaging - mrQA - Tools for quality assurance in medical imaging datasets, including protocol compliance. (Quality Assurance and Checking / MR)

README

        
mrQA : automatic protocol compliance checks on MR datasets

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.. image:: https://img.shields.io/pypi/v/mrQA.svg

        :target: https://pypi.python.org/pypi/mrQA

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        :target: https://app.codacy.com/gh/sinhaharsh/mrQA/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_grade

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.. image:: https://raw.githubusercontent.com/jupyter/design/master/logos/Badges/nbviewer_badge.svg

        :target: https://nbviewer.org/github/Open-Minds-Lab/mrQA/blob/master/examples/usage.ipynb

----

Documentation: https://open-minds-lab.github.io/mrQA/

----

``mrQA`` is a tool developed for automatic evaluation of protocol compliance in MRI datasets. The tool analyzes MR acquisition data from DICOM headers and compares it against protocol to determine the level of compliance. It takes as input a dataset in DICOM/BIDS format. The tool outputs a compliance report in HTML format, with a percent compliance score for each sequence/modality in a dataset. The tool also outputs a JSON file with the compliance scores for each modality. In addition, it highlights any deviations from the protocol. The tool has been specifically created keeping in mind those who directly acquired the data such as MR Physicists and Technologists, but can be used by anyone who wants to evaluate that MR scans are acquired according to a pre-defined protocol and to minimize errors in acquisition process.

``mrQA`` uses ``MRDataset`` to efficiently parse various neuroimaging dataset formats, which is available `here `_.

Key features:

- protocol compliance checks in key dimensions, both

   - horizontal audit (within-sequence across-dataset), as well as 

   - vertical audit (within-session across-sequence)

- continuous monitoring of incoming data (hourly or daily on XNAT server or similar)

- parallel processing of very large datasets (like ABCD or UK Biobank) on a HPC cluster

- few more to be released soon including automatic artefact detection and rating

Simple schematic of the library:

.. image:: ./docs/schematic_mrQA.png