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Automated, Open-Source, Vendor-Independent Quality Assurance Protocol Based on the Pulseq Framework

Neuroimaging research requires consistent image quality and temporal signal stability, especially for functional MRI studies that rely on detecting subtle BOLD signal changes. Regular MR system performance monitoring is essential, especially for longitudinal and multi-site studies. This study aims to establish a robust quality assurance (QA) protocol to promote data comparability across scanner models, vendors, and sites, as well as over a prolonged period.

This manuscript was submitted to the Special Issue Reproducibility and Quality Assurance of the Magnetic Resonance Materials in Physics, Biology and Medicine (MRMP) journal.

This repository hosts materials for

  • all reconstructed images,
  • instruction for data acquisition,
  • instruction for image reconstruction,
  • instruction for post-processing, and
  • example raw data and DICOM images.

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