Accelerated GVE File Parsing for Philips MRI Sequences Using Julia
Motivation: MRI simulation and reconstruction projects often require loading entire MRI sequences. Existing solutions in MATLAB tend to be slow and inefficient. Goal(s): This work aims to provide a fast Julia implementation for loading Philips GVE files containing all relevant MRI sequence parameters. Approach: We exploit Julia's superior file handling and multithreading capabilities to develop a module that can easily be integrated into other MRI projects. Performance and accuracy are evaluated by comparing to an existing MATLAB solution. Results: Our Julia module achieves acceleration factors up to 29.16 while maintaining a high accuracy of the loaded sequences. Impact: Long load times of MRI sequences can significantly slow down simulation and reconstruction projects. The proposed Julia module provides a fast and accurate solution that can easily be integrated into other projects.
Authors
- Christina Gräf (ORCID: https://orcid.org/0000-0002-3308-5640)
- Alexander Rauscher (ORCID: https://orcid.org/0000-0002-1961-8252)
- Alexander Jaffray (ORCID: https://orcid.org/0000-0002-9571-1838)
- Julian Kloiber
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2025-09-16
- DOI
- https://doi.org/10.58530/2025/1959
- Primary Topic
- Generative Adversarial Networks and Image Synthesis
- Type
- article
- Field-Weighted Citation Impact
- 0.00