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qrage

Quantitative Rapid Gradient-Echo Sequence

https://github.com/inm-4/qrage

Science Score: 75.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
    Found CITATION.cff file
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    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
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    DOI references
    Found 2 DOI reference(s) in README
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    Academic publication links
    Links to: wiley.com
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    Academic email domains
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    Institutional organization owner
    Organization inm-4 has institutional domain (www.fz-juelich.de)
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    Scientific vocabulary similarity
    Low similarity (9.7%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Quantitative Rapid Gradient-Echo Sequence

Basic Info
  • Host: GitHub
  • Owner: inm-4
  • License: agpl-3.0
  • Language: Jupyter Notebook
  • Default Branch: main
  • Homepage:
  • Size: 247 KB
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.md

QRAGE

This repository provides a Pulseq implementation of the QRAGE MRI sequence, as described in our publication:
"QRAGE—Simultaneous multiparametric quantitative MRI of water content, T1, T2*, and magnetic susceptibility at ultrahigh field strength".

How to Use This Repository

Follow these steps to set up and use QRAGE:

  1. Clone the QRAGE Repository

bash git clone https://github.com/inm-4/qrage.git cd qrage

  1. Install the Custom PyPulseq

QRAGE relies on modifications to PyPulseq that have not yet been merged upstream. You can install the custom PyPulseq in one of two ways:

  • Option A: Clone and Install Locally

    bash git clone https://github.com/inm-4/pypulseq.git cd pypulseq git checkout develop pip install -e .

  • Option B: Install Directly via pip

    bash pip install git+https://github.com/inm-4/pypulseq.git@devel

Differences from the Published Implementation

While we have worked diligently to replicate the QRAGE sequence originally developed in the SIEMENS IDEA framework, there are some minor differences between this implementation and the one used in the publication. For instance, the repetition time, inversion time, and echo times differ slightly. However, our comparisons indicate that these variations do not have a significant impact on image quality or the accuracy of the parameter maps.

Missing Content

Currently, this repository contains only the sequence implementation. We are actively working on open-sourcing the complete image reconstruction pipeline—including both pre-processing and post-processing steps—which will be available soon.

How to give credit

If you use this package, please acknowledge our work by citing:

Zimmermann M, Abbas Z, Sommer Y, et al. QRAGE—Simultaneous multiparametric quantitative MRI of water content, T1, T2*, and magnetic susceptibility at ultrahigh field strength. Magn Reson Med. 2025; 93(1): 228-244. doi: 10.1002/mrm.30272

A BibTeX file is directly contained within this package (QRAGE.bib).

Owner

  • Name: Institute of Neuroscience and Medicine - Medical Imaging Physics (INM-4)
  • Login: inm-4
  • Kind: organization
  • Location: Germany

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: Zimmermann
    given-names: Markus
    orcid: https://orcid.org/0000-0003-1273-5218
title: "QRAGE"
version: 0.0.1
identifiers:
  - type: doi
    value: TBD
date-released: TBD

GitHub Events

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Dependencies

pyproject.toml pypi
  • numpy >=2.1.3
  • pypulseq @ git+https://github.com/inm-4/pypulseq.git#devel