An Automatic Image Processing Workflow for Daily Magnetic Resonance Imaging Quality Assurance.

Area of Science:

• Medical Imaging
• Radiologic Technology
• Biomedical Engineering

Background:

• Magnetic resonance imaging (MRI) equipment requires regular quality assurance (QA) programs for performance monitoring.
• Current QA protocols involve various tests at different intervals, which can be time-consuming and labor-intensive, especially in multi-scanner environments.

Purpose of the Study:

• To develop and evaluate a fully automated daily MRI QA workflow.
• To minimize manual labor in the QA process while enhancing the efficiency and repeatability of scanner performance evaluation.

Main Methods:

• A daily QA system was developed using a phantom image acquired with standardized parameters and setup.
• Automated image analysis processes recorded parameters into performance metrics.
• A web-based interface presents processed data and graphs for accessible review.

Main Results:

• The automated workflow effectively measures multiple MRI scanner performance parameters with minimal manual intervention.
• The system provides time-series data for monitoring short- and long-term scanner stability.
• The automated approach reduces the laborious nature of manual daily QA.

Conclusions:

• The developed automated MRI QA system offers an efficient and repeatable method for monitoring scanner performance.
• This workflow streamlines the QA process, enabling better tracking of MRI equipment stability.
• The system facilitates improved reaction times and novel performance evaluation methods for MRI scanners.