An open-source reference system for portable low-field MRI designed to support replication, reproducibility, benchmarking, and quantitative comparison is presented, aiming to support cross-site comparability, reproducible research, and collaborative development of future portable low-field MRI technologies.
Abstract
Despite its renewed attention, the pathway to point-of-care portable low-field MRI systems remains challenging, limiting adoption across research groups. Incomplete documentation limits reproducibility, causing redesign and complicating cross-system comparison. Moreover, non-standardized testing and characterization complicates ethical approval for clinical studies. We present an open-source reference system for portable low-field MRI designed to support replication, reproducibility, benchmarking, and quantitative comparison. The system is fully open source, based on a ~50 mT permanent magnet, and integrated with a cloud-native acquisition platform. Pulseq-based calibration, characterization, and imaging sequences assessed noise level, eddy currents, image-based SNR, and geometric accuracy. Quantitative T1, T2, and B0 mapping sequences were developed and evaluated against reference values. Initial results from independent replications at two sites were compared. The system reached a noise level of 1.4 relative to the thermal noise floor and short eddy-current decay constants of 27-32 us across all gradient channels. Geometric deviations were below 2 mm over the field of view. Image-based SNR were consistent between the independent replications. Measured T1 values closely matched specified values, with an average absolute error of 3.1(1.8)%, while T2 values were overestimated by 10.4(5.8)%. Simulations showed only marginal errors for both quantities, suggesting experimental error sources for T2 mapping. The reference system combines openly documented hardware, software, calibration procedures, phantoms, quantitative MRI, and simulation tools in a reproducible ecosystem, aiming to support cross-site comparability, reproducible research, and collaborative development of future portable low-field MRI technologies.
This work presents an open-source, optimized solenoid head coil tailored for the 50 mT open-source scanner (OSII ONE v2.1), set the basis for a fully reliable and reproducible component for the open-source OSII ONE MRI scanner.
Umberto Zanovello, Julia Pfitzer, Ariane Ernst et al.· 1 citation
Qualitative similarities between volume measurements in adults and the questions of reproducibility through test-retest reliability and external validity using recent software updates to the Hyperfine Swoop system constitute a crucial foundation for the clinical utility of 64 mT MRI in monitoring brain volume loss over...
M. Stockbridge, Rex Wang, V. Neal et al.· Aperture Neuro· 0 citations
It is critical to acknowledge that, while low-field applications have found important roles in terms of quality, speed, and performance, higher-field-strength scanners will remain the diagnostic standard for the foreseeable future.
B. N. Delman, D. Lefton, Mark Finkelstein et al.· Journal of computer assisted...· 0 citations
The recent developments in ultra-low-field brain MRI are reviewed, which enable imaging in open environments and demonstrate initial clinical applicability in point-of-care settings, and future developments are envisioned to address the current limitations of image quality and contrast in ultra-low-field brain MRI syst...
Ed X. Wu, Yujiao Zhao, Yilong Liu et al.· Stroke· 1 citation
This review summarizes current knowledge on neuroimaging data harmonization, inter-scanner variability, radiomic feature repeatability, standardized QA procedures, and the challenges associated with integrating artificial intelligence into clinical workflows to highlight the need for unified methodologies, transparent...
D. Gogola, P. Szomolányi· Measurement Science Review· 0 citations
This work enables reproducibility of advanced computational MRI methods within a comprehensive end-to-end open-source framework and proves that quantitative MRI methods consisting of acquisition and reconstruction were successfully implemented in BART.
Daniel Mackner, Philip Schaten, Markus Huemer et al.· arXiv.org· 0 citations
Related blog posts
Microsoft Research Blog· microsoft.comOct 12, 2026
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 6, 2026
Writing as a participant and researcher, PhD student JS Tan SM ’22 has co-authored a new book about the rise of tech worker protests and the employer backlash that followed.
MIT News · Artificial Intelligence· news.mit.eduOct 2, 2026
Writing as a participant and researcher, PhD student JS Tan SM ’22 has co-authored a new book about the rise of tech worker protests and the employer backlash that followed.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.